Automatic thresholds for atrial tachyarrhythmia detection in an implantable medical device

ABSTRACT

A system for detecting an atrial tachyarrhythmia episode includes a medical device having sensing circuitry configured to receive a cardiac electrical signal from electrodes coupled to the medical device and a processor configured to detect an atrial tachyarrhythmia episode in response to a time duration of the cardiac electrical signal classified as an atrial tachyarrhythmia being greater than or equal to a first detection threshold. The processor is configured to determine if detection threshold adjustment criteria are met based on at least the detected first atrial tachyarrhythmia episode and adjust the first detection threshold to a second detection threshold different than the first detection threshold in response to the detection threshold adjustment criteria being met.

RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.15/588,810, filed May 8, 2017, entitled “AUTOMATIC THRESHOLDS FOR ATRIALTACHYARRHYTHMIA DETECTION IN AN IMPLANTABLE MEDICAL DEVICE” (publishedas U.S. Patent Pub. No. 2018/0028086), which claims the benefit of thefiling date of U.S. Provisional Patent Application No. 62/367,177, filedJul. 27, 2016, entitled “AUTOMATIC THRESHOLDS FOR ATRIAL TACHYARRHYTHMIADETECTION IN AN IMPLANTABLE MEDICAL DEVICE,” the content of both ofwhich is incorporated by reference in their entirety.

TECHNICAL FIELD

The disclosure relates generally to cardiac medical devices and, inparticular, to an implantable cardiac medical device and method forautomatically adjusting a threshold for detecting atrial tachyarrhythmiaepisodes from sensed cardiac electrical signals.

BACKGROUND

During normal sinus rhythm (NSR), the heart beat is regulated byelectrical signals produced by the sino-atrial (SA) node located in theright atrial wall. Each atrial depolarization signal produced by the SAnode spreads across the atria, causing the depolarization andcontraction of the atria, and arrives at the atrioventricular (A-V)node. The A-V node responds by propagating a ventricular depolarizationsignal through the bundle of His of the ventricular septum andthereafter to the bundle branches and the Purkinje muscle fibers of theright and left ventricles.

Atrial tachyarrhythmia includes the disorganized form of atrialfibrillation and varying degrees of organized atrial tachycardia,including atrial flutter. Atrial fibrillation (AF) occurs because ofmultiple focal triggers in the atrium or because of changes in thesubstrate of the atrium causing heterogeneities in conduction throughdifferent regions of the atria. The ectopic triggers can originateanywhere in the left or right atrium or pulmonary veins. The AV nodewill be bombarded by frequent and irregular atrial activations but willonly conduct a depolarization signal when the AV node is not refractory.The ventricular cycle lengths will be irregular and will depend on thedifferent states of refractoriness of the AV-node.

As more serious consequences of persistent atrial arrhythmias have cometo be understood, such as an associated risk of relatively more seriousventricular arrhythmias and stroke, there is a growing interest inmonitoring and treating atrial arrhythmias. Implantable cardiac monitorsand implantable cardioverter defibrillators (ICDs) may be configured toacquire cardiac electrical signals that can be analyzed for detectingatrial arrhythmias.

SUMMARY

In general, the disclosure is directed to techniques for detectingatrial tachyarrhythmia episodes by an implantable medical device. Amedical device operating according to the techniques disclosed hereinanalyzes a cardiac electrical signal over a plurality of time periodsand classifies each of the time periods based on characteristics of thecardiac electrical signal, such as characteristics of the RR-intervalsoccurring during each of the plurality of time periods. The device mayautomatically adjust a threshold number of time periods that areclassified as atrial tachyarrhythmia which are required in order todetect the atrial tachyarrhythmia.

In one example, the disclosure provides a method for detecting an atrialtachyarrhythmia episode by a medical device, comprising receiving acardiac electrical signal via electrodes coupled to sensing circuitry ofthe medical device, detecting an atrial tachyarrhythmia episode by aprocessor of the medical device in response to a time duration of thecardiac electrical signal classified as an atrial tachyarrhythmia beinggreater than or equal to a first detection threshold, determining ifdetection threshold adjustment criteria are met based on at least thedetected atrial tachyarrhythmia episode; and adjusting the firstdetection threshold to a second detection threshold different than thefirst detection threshold in response to the detection thresholdadjustment criteria being met.

In another example, the disclosure provides a medical device fordetecting an atrial tachyarrhythmia. The medical device includes sensingcircuitry configured to receive a cardiac electrical signal fromelectrodes coupled to the sensing circuitry, and a processor configuredto detect an atrial tachyarrhythmia episode in response to a timeduration of the cardiac electrical signal classified as an atrialtachyarrhythmia being greater than or equal to a first detectionthreshold, determine if detection threshold adjustment criteria are metbased on at least the detected atrial tachyarrhythmia episode, andadjust the first detection threshold to a second detection thresholddifferent than the first detection threshold in response to thedetection threshold adjustment criteria being met.

In another example, the disclosure provides a non-transitory,computer-readable storage medium storing instructions for causing aprocessor included in a medical device to perform a method for detectingan atrial tachyarrhythmia episode. The method includes receiving acardiac electrical signal via electrodes coupled to sensing circuitry ofthe medical device, detecting an atrial tachyarrhythmia episode inresponse to a time duration of the cardiac electrical signal classifiedas an atrial tachyarrhythmia being greater than or equal to a firstdetection threshold, determining if detection threshold adjustmentcriteria are met based on at least the detected atrial tachyarrhythmiaepisode, and adjusting the first detection threshold to a seconddetection threshold different than the first detection threshold inresponse to the detection threshold adjustment criteria being met.

This summary is intended to provide an overview of the subject matterdescribed in this disclosure. It is not intended to provide an exclusiveor exhaustive explanation of the apparatus and methods described indetail within the accompanying drawings and description below. Furtherdetails of one or more examples are set forth in the accompanyingdrawings and the description below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual diagram of an implantable cardioverterdefibrillator (ICD) system for detecting atrial arrhythmias according toone example.

FIGS. 2A and 2B are conceptual diagrams of an alternative ICD systemthat may be configured to detect atrial tachyarrhythmia according to thetechniques disclosed herein.

FIG. 3 is a conceptual diagram of an implantable medical device (IMD)system for detecting atrial tachyarrhythmia according to anotherexample.

FIG. 4 is a functional schematic diagram of an ICD, such as the ICD ofFIG. 1 or the ICD of FIGS. 2A and 2B.

FIG. 5 is a schematic diagram of methods used for detecting cardiacevents by any of the ICDs of FIGS. 1A, 1B and 2 or the monitoring deviceof FIG. 1C according to one example.

FIG. 6 is a diagram of a two-dimensional histogram representing a Lorenzplot area used in the techniques disclosed herein for detecting atrialtachyarrhythmia.

FIG. 7 is flowchart of a method for determining a factor for classifyingtime periods for detecting atrial tachyarrhythmia according to oneexample.

FIG. 8 is a flowchart of a method for classifying a predetermined timeperiod for use in detecting atrial tachyarrhythmia according to oneexample.

FIG. 9 is a schematic diagram of atrial fibrillation detection that maybe performed by the ICDs shown in FIGS. 1, 2A and 2B or the monitor ofFIG. 3.

FIG. 10 is a schematic diagram of a method for detecting atrialfibrillation by an ICD or implantable monitoring device according toanother example.

FIG. 11 is a flowchart of a method for detecting atrial fibrillation,according to one example.

FIG. 12 is a flow chart of a method performed by an ICD or implantablemonitor for providing a response to detecting atrial tachyarrhythmiaaccording to one example.

FIG. 13 is a flow chart of a method performed by an implantable medicaldevice system, such as the ICD system of FIG. 1 or the ICD system ofFIGS. 2A and 2B, for automatically adjusting a detection thresholdrequired to detect an atrial tachyarrhythmia, such as AF.

FIG. 14 is a flow chart of a method for automatically adjusting adetection threshold for detecting AF according to another example.

FIG. 15 is a flow chart of a method for detecting AF and determining AFburden according to another example.

FIG. 16 is a flow chart of a method for storing AF episode data in thememory of an ICD according to one example.

DETAILED DESCRIPTION

In the following description, references are made to illustrativeexamples for carrying out the methods described herein. It is understoodthat other variations from these examples may be utilized withoutdeparting from the scope of the disclosure. In these various examples, acardiac electrical signal is used for determining successive ventricularcycle lengths for use in detecting atrial arrhythmias. Ventricular cyclelengths may be determined as intervals between successive R-waves thatare sensed from the cardiac electrical signal and attendant to thedepolarization of the ventricles. The differences between the successiveventricular cycle lengths, or RR intervals (RRIs), are analyzed fordetermining evidence of atrial tachyarrhythmia, e.g., atrialfibrillation (AF). As described herein, a time period of the cardiacsignal may be classified as AF, non-AF, or unclassified based on ananalysis of the RRIs and other factors. When a predetermined number oftime periods of the cardiac signal are classified as AF, a medicaldevice operating according to the techniques disclosed herein may detectan AF episode. The device, however, may adjust a classificationcriterion applied for classifying a time period of the cardiac signalprior to detecting AF and detect AF based on the adjusted classificationcriterion used for classifying subsequent time periods. Furthermore, thedevice may automatically adjust the number of time periods required tobe classified as AF in order to detect the AF episode.

Aspects of the methods described herein can be incorporated in a varietyof implantable or external medical devices having cardiac signalmonitoring capabilities, which may or may not include therapy deliverycapabilities. Such devices include single chamber, dual chamber orbi-ventricular pacing systems or ICDs that sense the R-waves and deliveran electrical stimulation therapy to the ventricles. The atrialarrhythmia detection methods presently disclosed may also beincorporated in implantable cardiac monitors having implantableelectrodes or external cardiac monitors having electrocardiogram (ECG)electrodes coupled to the patient's skin to detect R-waves, e.g., Holtermonitors, or within computerized systems that analyze pre-recorded ECGor cardiac electrogram (EGM) data. Embodiments may further beimplemented in a patient monitoring system, such as a centralizedcomputer system which processes cardiac electrical signals and otherdata sent to it by implantable or wearable monitoring devices.

FIG. 1 is a conceptual diagram of an implantable medical device (IMD)system 1 for detecting atrial tachyarrhythmias according to one example.The IMD system 1 includes an implantable cardioverter defibrillator(ICD) 10 coupled to a patient's heart 2 via a transvenous electricalmedical lead 16. ICD 10 includes a connector block 12 that may beconfigured to receive the proximal end of lead 16, which is advancedtransvenously for positioning electrodes for sensing and stimulation inthe right ventricular chamber of heart 2 in the example shown. Thetechniques disclosed herein may be implemented in a single chamber ICDsystem 1 that is coupled only to a ventricular lead such as rightventricular (RV) lead 16 for receiving cardiac electrical signalsincluding at least R-waves attendant to the ventricular depolarizationsof heart 2.

RV lead 16 is positioned such that its distal end is in the rightventricle for sensing RV cardiac signals and delivering pacing orshocking pulses in the right ventricle. For these purposes, RV lead 16is equipped with pacing and sensing electrodes shown as a ring electrode30 and a tip electrode 28. In some examples, tip electrode 28 is anextendable helix electrode mounted retractably within an electrode head.RV lead 16 is further shown to carry defibrillation electrodes 24 and26, which may be elongated coil electrodes used to deliver high voltagecardioversion/defibrillation (CV/DF) shocks. Defibrillation electrode 24is referred to herein as the “RV defibrillation electrode ” or “RV coilelectrode” because it may be carried along RV lead 16 such that it ispositioned substantially within the right ventricle when distal pacingand sensing electrodes 28 and 30 are positioned for pacing and sensingin the right ventricle. Defibrillation electrode 26 is referred toherein as a “superior vena cava (SVC) defibrillation electrode” or “SVCcoil electrode” because it may be carried along RV lead 16 such that itis positioned at least partially along the SVC when the distal end of RVlead 16 is advanced within the right ventricle.

Each of electrodes 24, 26, 28 and 30 are connected to a respectiveinsulated conductor extending within the body of lead 16. The proximalend of the insulated conductors are coupled to corresponding connectorscarried by a proximal lead connector assembly, e.g., an industrystandard DF-4 connector, at the proximal end of lead 16, which may beinserted into a connector bore of connector block 12 for providingelectrical connection to ICD 10.

The techniques disclosed herein for detecting atrial tachyarrhythmia maybe successfully performed without requiring atrial signal sensing. Assuch, these techniques may be implemented in a single chamber ICDsystem, such as system 1, which includes a lead extending into the rightventricle for positioning electrodes for sensing ventricular signals butdoes not include electrodes positioned in or along the atrial chambersfor sensing atrial signals. In other examples, other transvenous leadsmay be present, e.g., a right atrial lead for sensing right atrialsignals and delivering electrical stimulation pulses to the rightatrium, and/or a left ventricular lead, which may be advancedtransvenously into a cardiac vein via the coronary sinus, for sensingleft ventricular signals and delivering electrical stimulation pulses tothe left atrium. A multi-chamber ICD system in which aspects of thetechniques described herein is generally disclosed in U.S. patentapplication Ser. No. 14/520,798, (Cao et al.), incorporated herein byreference in their entirety.

Electrodes 28 and 30 (and/or coil electrodes 24 and 26) may be used foracquiring cardiac electrical signals needed for performing atrialtachyarrhythmia detection as described herein. R-waves sensed fromcardiac electrical signals obtained by ICD 10 are used for determiningRRIs between consecutively sensed R-waves for detecting atrialtachyarrhythmia by a processor of ICD 10 based at least in part on ananalysis of the RRIs. ICD 10 may be configured to sense cardiacelectrical signals from electrodes 24, 26, 28 and/or 30, detect atrialtachyarrhythmia and provide an atrial tachyarrhythmia detection responsesuch as storing atrial tachyarrhythmia episode data for transmission toan external device 40. ICD 10 may additionally be configured to deliverventricular bradycardia pacing, detect ventricular tachyarrhythmias, anddeliver anti-tachycardia pacing therapy and cardioversion/defibrillationshock therapies to the RV via electrodes 24, 26, 28 and/or 30 carried bylead 16.

The RV pacing and sensing electrodes 28 and 30 may be used as a bipolarpair, commonly referred to as a “tip-to-ring” configuration for sensingcardiac electrical signals. In some cases, RV tip electrode 28 may beselected with a coil electrode 24 or 26 to be used as an integratedbipolar pair, commonly referred to as a “tip-to-coil” configuration forsensing cardiac electrical signals. ICD 10 may, for example, select oneor more sensing electrode vectors including a tip-to-ring sensing vectorbetween electrodes 28 and 30 and a tip-to-coil or ring-to-coil sensingvector, e.g., between RV tip electrode 28 and SVC coil electrode 26,between RV tip electrode 28 and RV coil electrode 24, between RV ringelectrode 30 and SVC coil electrode 26 or between RV ring electrode 30and RV coil electrode 24. In other examples, any of the electrodes 24,26, 28 or 30 carried by RV lead 16 may be selected by ICD 10 in aunipolar sensing configuration with the ICD housing 15 serving as theindifferent electrode, commonly referred to as the “can” or “case”electrode. It is recognized that numerous sensing and electricalstimulation electrode vectors may be available using the variouselectrodes carried by lead 16 and coupled to ICD 10. ICD 10 may beconfigured to selectively couple one or more sensing electrode vectorsto sensing circuitry enclosed by housing 15, e.g., sensing circuitryincluding one or more amplifiers, filters, rectifiers, comparators,sense amplifiers, analog-to-digital convertors and/or other circuitryconfigured to acquire a cardiac electrical signal for use in detectingcardiac arrhythmias.

In other examples, the ICD housing 15 may serve as a subcutaneousdefibrillation electrode in combination with one or both of the coilelectrodes 24 and/or 26 for delivering CV/DF shocks to the atria orventricles. It is recognized that alternate lead systems may besubstituted for the single RV lead system illustrated in FIG. 1. While aparticular single-chamber ICD and transvenous lead system 1 isillustrated in FIG. 1, methodologies included in the present disclosuremay be adapted for use with any single chamber, dual chamber, ormulti-chamber ICD or pacemaker system, subcutaneous implantable device,or other internal or external cardiac monitoring device.

An external device 40 is shown in telemetric communication with ICD 10by an RF communication link 42. External device 40 is often referred toas a “programmer” because it is typically used by a physician,technician, nurse, clinician or other qualified user for programmingoperating parameters in ICD 10. External device 40 may be located in aclinic, hospital or other medical facility. External device 40 mayalternatively be embodied as a home monitor or a handheld device thatmay be used in a medical facility, in the patient's home, or anotherlocation. Operating parameters, such as sensing and therapy deliverycontrol parameters, may be programmed into ICD 10 using external device40.

External device 40 includes a processor 52, memory 53, user display 54,user interface 56 and telemetry circuitry 58. Processor 52 controlsexternal device operations and processes data and signals received fromICD 10. According to techniques disclosed herein, processor 52 mayreceive atrial tachyarrhythmia data obtained by ICD 10 and transmittedfrom ICD 10 to external telemetry circuitry 58. As described below inconjunction with FIGS. 12 and 16, ICD 10 may be configured to storecardiac signal data associated with detected atrial tachyarrhythmiaepisodes and transmit the cardiac signal data to external device 40.Processor 52 provides user display 54 with at least a portion of thecardiac electrical signal data for generating a display of the cardiacelectrical signal detected as atrial tachyarrhythmia for observation andreview by a clinician.

The user display 54 provides a display of the cardiac signal data andmay include a graphical user interface that facilitates programming ofone or more sensing parameters and/or atrial arrhythmia detectionparameters as well as other arrhythmia detection and therapy controlparameters by a user interacting with external device 40. Externaldevice 40 may display other data and information relating to ICDfunctions to a user for reviewing ICD operation and programmedparameters as well as cardiac electrical signals or other physiologicaldata that is retrieved from ICD 10 during an interrogation session. Userinterface 56 may include a mouse, touch screen, or other pointingdevice, keyboard and/or keypad to enable a user to interact withexternal device 40 to initiate a telemetry session with ICD 10 forretrieving data from and/or transmitting data to ICD 10 and forselecting and programming desired sensing and therapy delivery controlparameters into ICD 10.

Telemetry circuitry 58 includes a transceiver and antenna configured forbidirectional communication with an implantable transceiver and antennaincluded in ICD 10. Telemetry circuitry 58 is configured to operate inconjunction with processor 52 for encoding and decoding transmitted andreceived data relating to ICD functions via communication link 42.Communication link 42 may be established between ICD 10 and externaldevice 40 using a radio frequency (RF) link such as BLUETOOTH®, Wi-Fi,Medical Implant Communication Service (MICS) or other RF bandwidth. Insome examples, external device 40 may include a programming head that isplaced proximate ICD 10 to establish and maintain a communication link,and in other examples external device 40 and ICD 10 may be configured tocommunicate using a distance telemetry algorithm and circuitry that doesnot require the use of a programming head and does not require userintervention to maintain a communication link.

It is contemplated that external device 40 may be in wired or wirelessconnection to a communications network via telemetry circuitry 58 fortransferring data to a remote database or computer to allow remotemanagement of the patient 3. Remote patient management systems may beconfigured to utilize the presently disclosed techniques to enable aclinician to review cardiac electrical signal data and atrialtachyarrhythmia episode data received from ICD 10 and to select andprogram control parameters transmitted to ICD 10. Reference is made tocommonly-assigned U.S. Pat. No. 6,599,250 (Webb et al.), U.S. Pat. No.6,442,433 (Linberg et al.), U.S. Pat. No. 6,418,346 (Nelson et al.), andU.S. Pat. No. 6,480,745 (Nelson et al.) for general descriptions andexamples of remote patient management systems that enable remote patientmonitoring and device programming. Each of these patents is incorporatedherein by reference in their entirety.

FIGS. 2A and 2B are conceptual diagrams of an alternative ICD system 100that may be configured to detect atria arrhythmias according to thetechniques disclosed herein. FIG. 2A is a front view of anextra-cardiovascular ICD system 100 implanted within patient 112. FIG.2B is a side view of ICD system 100 implanted within patient 112. ICDsystem 100 includes an ICD 110 connected to an extra-cardiovascularelectrical stimulation and sensing lead 116. ICD system 100 may furtherinclude an intracardiac pacemaker 101 configured to deliver pacingpulses to a heart chamber, for example from within the right ventricleor within the left ventricle.

ICD 110 includes a housing 115 that forms a hermetic seal that protectsinternal components of ICD 110. Internal device components may includecircuitry shown and described in conjunction with FIG. 4 below, such assense amplifier(s), A/D converter, pacing output circuitry, high voltageoutput circuitry and a microprocessor and memory and/or other controlcircuitry. The housing 115 of ICD 110 may be formed of a conductivematerial, such as titanium or titanium alloy. The housing 115 mayfunction as a housing electrode (sometimes referred to as a canelectrode). In examples described herein, housing 115 may be used as anactive can electrode for use in delivering cardioversion/defibrillation(CV/DF) shocks or other high voltage pulses generated by high voltagecharging circuitry of ICD 110. In other examples, housing 115 may beavailable for use in sensing cardiac signals and/or for deliveringunipolar, low voltage cardiac pacing pulses by a pacer output circuit inconjunction with lead-based cathode electrodes. In other instances, thehousing 115 of ICD 110 may include multiple electrodes on an outerportion of the housing. The outer portion(s) of the housing 115functioning as an electrode(s) may be coated with a material, such astitanium nitride.

ICD 110 includes a connector assembly 117 (also referred to as aconnector block or header) that includes electrical feedthroughscrossing housing 115 to provide electrical connections betweenconductors extending within the lead body 118 of lead 116 and electroniccomponents included within the housing 115 of ICD 110. As describedbelow in conjunction with FIG. 4, housing 115 may house one or moreprocessors, memories, telemetry transceivers, sensing circuitry such assense amplifiers and analog-to digital converters, therapy deliverycircuitry such as pacer timing and control, CV/DF control, pace outputand HV output circuits and associated charging circuits, a switchmatrix, a data bus, one or more batteries or other power sources andother components for sensing cardiac electrical signals, detecting aheart rhythm, and controlling and delivering electrical stimulationpulses to treat an abnormal heart rhythm.

Lead 116 includes an elongated lead body 118 having a proximal end 127that includes a lead connector (not shown) configured to be connected toICD connector assembly 117 and a distal portion 125 that includes one ormore electrodes. In the example illustrated in FIGS. 2A and 2B, thedistal portion 125 of lead 116 includes defibrillation electrodes 124and 126 and pace/sense electrodes 128, 130 and 131. Electricalconductors (not illustrated) extend through one or more lumens of theelongated lead body 118 of lead 116 from the lead connector at theproximal lead end 127 to electrodes 124, 126, 128, 130 and 131 locatedalong the distal portion 125 of the lead body 118. The lead body 118 oflead 116 may be formed from a non-conductive material, includingsilicone, polyurethane, fluoropolymers, mixtures thereof, and otherappropriate materials, and shaped to form one or more lumens withinwhich the one or more conductors extend. However, the techniquesdisclosed herein are not limited to such constructions or to anyparticular lead body design.

The respective conductors electrically couple the electrodes 124, 126,128, 130 and 131 to circuitry, such as a switch matrix or otherswitching circuitry for selection and coupling to a sense amplifier orother cardiac event detection circuitry and/or to a therapy outputcircuit, e.g., a pacing output circuit or a HV output circuit fordelivering CV/DF shock pulses. Connections between electrode conductorsand ICD circuitry is made via connections in the connector assembly 117,including associated electrical feedthroughs crossing housing 115. Theelectrical conductors transmit therapy from an output circuit within ICD110 to one or more of defibrillation electrodes 124 and 126 and/orpace/sense electrodes 128, 130 and 131 and transmit sensed electricalsignals from one or more of defibrillation electrodes 124 and 126 and/orpace/sense electrodes 128, 130 and 131 to the sensing circuitry withinICD 110.

ICD 110 may obtain electrical signals corresponding to electricalactivity of heart 102 via a combination of sensing vectors that includecombinations of electrodes 128, 130, and/or 131. In some examples,housing 115 of ICD 110 is used in combination with one or more ofelectrodes 128, 130 and/or 131 in a sensing electrode vector. ICD 110may even obtain cardiac electrical signals using a sensing vector thatincludes one or both defibrillation electrodes 124 and/or 126, e.g.,between electrodes 124 and 126 or one of electrodes 124 or 126 incombination with one or more of electrodes 128, 130, 131, and/or thehousing 115.

ICD 110 analyzes the cardiac electrical signals received from one ormore of the sensing vectors to monitor for abnormal rhythms, such as AF,VT and VF. ICD 110 generates and delivers electrical stimulation therapyin response to detecting a ventricular tachyarrhythmia (e.g., VT or VF).ICD 110 may deliver ATP in response to VT detection, and in some casesmay deliver ATP prior to a CV/DF shock or during high voltage capacitorcharging in an attempt to avert the need for delivering a CV/DF shock.ICD 110 may deliver a CV/DF shock pulse when VF is detected or when VTis not terminated by ATP.

Electrodes 124 and 126 (and in some examples housing 115) are referredto herein as defibrillation electrodes because they are utilized,individually or collectively, for delivering high voltage stimulationtherapy (e.g., cardioversion or defibrillation shocks). Electrodes 124and 126 may be elongated coil electrodes and generally have a relativelyhigh surface area for delivering high voltage electrical stimulationpulses compared to low voltage pacing and sensing electrodes 28, 30 and31. However, electrodes 124 and 126 and housing 115 may also be utilizedto provide pacing functionality, sensing functionality or both pacingand sensing functionality in addition to or instead of high voltagestimulation therapy. In this sense, the use of the term “defibrillationelectrode” herein should not be considered as limiting the electrodes124 and 126 for use in only high voltage cardioversion/defibrillationshock therapy applications. Electrodes 124 and 126 may be used in apacing electrode vector for delivering extra-cardiovascular pacingpulses such as ATP pulses, post-shock pacing or other pacing therapiesand/or in a sensing vector used to sense cardiac electrical signals fordetecting atrial and ventricular arrhythmias, including AF, atrialflutter, VT and VF.

Electrodes 128, 130 and 131 are relatively smaller surface areaelectrodes for delivering low voltage pacing pulses and for sensingcardiac electrical signals. Electrodes 128, 130 and 131 are referred toas pace/sense electrodes because they are generally configured for usein low voltage applications, e.g., used as either a cathode or anode fordelivery of pacing pulses and/or sensing of cardiac electrical signals.

The pace/sense electrodes 128, 130 and/or 131 may be located atdifferent locations along the length of lead 116 than shown. In otherexamples, lead 116 may include less than three pace/sense electrodes ormore than three pace/sense electrodes and/or a single defibrillationelectrode or more than two electrically isolated or electrically coupleddefibrillation electrodes or electrode segments. Various exampleconfigurations of extra-cardiovascular leads and electrodes anddimensions that may be implemented in conjunction with the AF detectiontechniques disclosed herein are described in commonly-assigned U.S. Pat.application Ser. No. 14/519,436, U.S. patent application Ser. No.14/695,255 and provisionally-filed U.S. Pat. Application No. 62/089,417,all of which are incorporated herein by reference in their entirety.

Lead 16 extends subcutaneously or submuscularly over the ribcage 132medially from the connector assembly 127 of ICD 110 toward a center ofthe torso of patient 112, e.g., toward xiphoid process 120 of patient112. At a location near xiphoid process 120, lead 116 bends or turns andextends superiorly within anterior mediastinum 136 in a substernalposition. Lead 116 of system 100 is implanted at least partiallyunderneath sternum 122 of patient 112.

Anterior mediastinum 136 may be viewed as being bounded laterally bypleurae, posteriorly by pericardium 138, and anteriorly by sternum 122.In some instances, the anterior wall of anterior mediastinum 136 mayalso be formed by the transversus thoracis muscle and one or more costalcartilages. Anterior mediastinum 136 includes a quantity of looseconnective tissue (such as areolar tissue), adipose tissue, some lymphvessels, lymph glands, substernal musculature, small side branches ofthe internal thoracic artery or vein, and the thymus gland. In oneexample, the distal portion 125 of lead 116 extends along the posteriorside of sternum 122 substantially within the loose connective tissueand/or substernal musculature of anterior mediastinum 136.

A lead implanted such that the distal portion 125 is substantiallywithin anterior mediastinum 136 may be referred to as a “substernallead.” In the example illustrated in FIGS. 2A and 2B, lead 116 extendssubstantially centered under sternum 122. In other instances, however,lead 116 may be implanted such that it extends in a position that isoffset laterally from the center of sternum 122. In some instances, lead116 may extend laterally such that distal portion 125 of lead 116 isunderneath/below the ribcage 132 in addition to or instead of sternum122. In other examples, the distal portion 125 of lead 116 may beimplanted in other extra-cardiovascular, intra-thoracic locations,including the pleural cavity or around the perimeter of and adjacent tobut typically not within the pericardium 138 of heart 102.

In other examples, lead 116 may remain outside the thoracic cavity andextend subcutaneously or submuscularly over the ribcage 132 and/orsternum 122. The path of lead 116 may depend on the location of ICD 110,the arrangement and position of electrodes carried by the lead distalportion 125, and/or other factors.

ICD 110 is shown implanted subcutaneously on the left side of patient112 along the ribcage 132. ICD 110 may, in some instances, be implantedbetween the left posterior axillary line and the left anterior axillaryline of patient 112. ICD 110 may, however, be implanted at othersubcutaneous or submuscular locations in patient 112. For example, ICD110 may be implanted in a subcutaneous pocket in the pectoral region. Inthis case, lead 116 may extend subcutaneously or submuscularly from ICD110 toward the manubrium of sternum 122 and bend or turn and extendinferior from the manubrium to the desired location subcutaneously orsubmuscularly. In yet another example, ICD 110 may be placedabdominally.

In some patients, an intracardiac pacemaker 101 may be present in theright ventricle, right atrium or along the left ventricle. Pacemaker 101may be configured to deliver pacing pulses in the absence of sensedintrinsic heart beats, in response to detecting VT, or according toother pacing therapy algorithms. For example, pacemaker 101 may beimplanted in the right ventricle of the patient for providing singlechamber ventricular pacing. The techniques disclosed herein forclassifying time periods of a cardiac signal for detecting atrialtachyarrhythmia may be utilized in the presence of ventricular pacingdelivered by ICD 110 and/or by an intracardiac pacemaker such aspacemaker 101. Pacemaker 101 may generally correspond to theintra-cardiac pacemaker disclosed in U.S. Pat. No. 8,923,963 (Bonner, etal.), incorporated herein by reference in its entirety. ICD 110 may beconfigured to detect pacing pulses delivered by pacemaker 101. Thefrequency of pacing pulses delivered by pacemaker 101 may be a factordetermined in classifying a cardiac electrical signal time period for AFdetection purposes.

Pacemaker 101 may have limited processing power and therapy deliverycapacity compared to ICD 110 such that the advanced cardiac rhythmdetection techniques disclosed herein may be implemented in ICD 110rather than in pacemaker 101. The methods disclosed herein as beingperformed by ICD 10 or ICD 110, however, are not to be consideredlimited to being implemented in an ICD. Aspects of the atrialtachyarrhythmia detection techniques disclosed herein may be implementedin pacemaker 101, all or in part.

FIG. 3 is a conceptual diagram of a cardiac monitoring device 60 whichmay employ aspects of the atrial tachyarrhythmia detection techniquesdisclosed herein. Monitoring device 60 is shown implanted subcutaneouslyin the upper thoracic region of a patient's body 3 and displaced fromthe patient's heart 2. The housing 62 of cardiac monitor 60 (shownenlarged in scale compared to the patient's body 3) includes anon-conductive header module 64 attached to a hermetically sealedhousing 62. The housing 62 contains the circuitry of the cardiac monitor60 and is generally electrically conductive but may be covered in partby an electrically insulating coating. A first, subcutaneous, senseelectrode, A, is formed on the surface of the header module 64. In someexamples, one or more electrodes may be incorporated in the headermodule 64. A second, subcutaneous, sense electrode, B, is formed by atleast a portion of the housing 62. For example, electrode B may be anexposed portion of housing 62 when housing 62 is coated by anelectrically insulating coating. The conductive housing electrode B maybe directly connected with the sensing circuitry.

An electrical feedthrough extends through the mating surfaces of theheader module 64 and the housing 62 to electrically connect the firstsense electrode A with sensing circuitry enclosed within the housing 62.The electrical signals attendant to the depolarization andre-polarization of the heart 2 are referred to as the cardiac electricalsignals and are sensed across the sense electrodes A and B and includeat least R-waves attendant to the ventricular depolarizations of heart2. The cardiac monitoring device 60 may be sutured to subcutaneoustissue at a desired orientation of its electrodes A and B to the axis ofthe heart 2 to detect and record the cardiac electrical signals in asensing vector A-B for subsequent processing and uplink telemetrytransmission to an external device 40 (shown in FIG. 1A).

In one embodiment, the spacing between electrodes A and B may range from60 mm to 25 mm. In other embodiments, the electrode spacing may rangefrom 55 mm to 30 mm, or from 55 mm to 35 mm. The volume of theimplantable cardiac monitoring device 60 may be three cubic centimetersor less, 1.5 cubic centimeters or less or any volume between three and1.5 cubic centimeters. The length of cardiac monitoring device 60 mayrange from 30 to 70 mm, 40 to 60 mm or 45 to 60 mm and may be any lengthbetween 30 and 70 mm. The width of a major surface such a cardiacmonitoring device 60 may range from 3 to 10 mm and may be any thicknessbetween 3 and 10 mm. The thickness of cardiac monitoring device 60 mayrange from 2 to 9 mm or 2 to 5 mm and may be any thickness between 2 and9 mm.

The sensing circuitry included in housing 62 is configured to detectR-waves for monitoring for atrial tachyarrhythmia according to thetechniques disclosed herein. Such sensing circuitry may include apre-filter and amplifier, an analog-to-digital filter, a rectifier, asense amplifier, a comparator and/or other components configured toreceive cardiac electrical signals and detect R-waves from the signals.Aspects of a cardiac monitoring device of the type that may employatrial tachyarrhythmia detection techniques disclosed herein aregenerally disclosed in U.S. Publication No. 2015/0088216 (Gordon, etal.) and U.S. Pat. No. 7,027,858 (Cao, et al.), both incorporated hereinby reference in its entirety.

In general, the hermetically sealed housing 62 includes a lithiumbattery or other power source, a processor and memory or other controlcircuitry that controls device operations and records arrhythmic cardiacelectrical signal episode data in memory registers or bins, and atelemetry transceiver and antenna circuit that receives downlinktelemetry commands from and transmits stored data in a telemetry uplinkto an external device 40 (FIG. 1). The circuitry and memory may beimplemented in discrete logic or a micro-computer based system with A/Dconversion of sampled cardiac electrical signal amplitude values. Oneimplantable cardiac monitor that can be modified in accordance with thepresently disclosed techniques is described in U.S. Pat. No. 6,412,490(Lee et al.), incorporated herein by reference in its entirety, as wellas the cardiac monitors disclosed in any of the above-incorporatedreferences.

FIG. 4 is a functional schematic diagram of an ICD, such as ICD 10 ofFIG. 1 or ICD 110 of FIGS. 2A and 2B. This diagram should be taken asillustrative of the type of device with which the techniques disclosedherein may be embodied and not as limiting. The example shown in FIG. 4is a microprocessor-controlled device, but the disclosed methods mayalso be practiced with other types of devices such as those employingdedicated digital circuitry.

With regard to the electrode system illustrated in FIG. 1, ICD 10 isprovided with a number of connection terminals for achieving electricalconnection to the RV lead 6 and its respective electrodes. Housing 15may be used as an indifferent electrode during unipolar stimulation orsensing or as an active can electrode during shock delivery. Electrodes24, 26 and housing 15 may be selectively coupled to the high voltageoutput circuit 234 to facilitate the delivery of high energy shockingpulses to the heart using one or more of the coil electrodes 24 and 26and optionally the housing 15.

RV tip electrode 28 and the RV ring electrode 30 may be coupled to aventricular sense amplifier 200 for sensing ventricular signals. Theventricular sense amplifier 200 may take the form of automatic gaincontrolled amplifiers with adjustable sensitivity. ICD 10 and, morespecifically, microprocessor 224 may automatically adjust thesensitivity of ventricular sense amplifier 200 in response to detectionof oversensing in order to reduce the likelihood of oversensing ofcardiac events and/or non-cardiac noise.

Ventricular sense amplifier 200 may receive timing information frompacer timing and control circuitry 212. For example, ventricular senseamplifier 200 may receive blanking period input, e.g., V_BLANK, whichindicates the amount of time the amplifier is “turned off” in order toprevent saturation due to an applied pacing pulse or defibrillationshock. The general operation of the ventricular sense amplifier 200 maycorrespond to that disclosed in U.S. Pat. No. 5,117,824 (Keimel, etal.), incorporated herein by reference in its entirety.

Whenever a signal received by ventricular sense amplifier 200 exceeds aventricular sensitivity, a signal is generated on the R-out signal line202. As described below, a signal on the R-out signal line 202, whichmay be referred to as a ventricular sense event (Vs event) signal, maybe received by microprocessor 224 and used for determining RRIdifferences.

Switch matrix 208 is used to select which of the available electrodes24, 26, 28 and 30 (or 124, 126, 128 and 130 of FIG. 2A) are coupled to awide band amplifier 210 for use in digital signal analysis. Selection ofthe electrodes is controlled by the microprocessor 224 via data/addressbus 218. The selected electrode configuration may be varied as desiredfor the various sensing, pacing, cardioversion and defibrillationfunctions of the ICD 10. For example, while RV electrodes 28 and 30 areshown coupled to sense amplifier 200 and pace output circuit 216suggesting dedicated pace/sense electrodes and coil electrodes 24 and 26are shown coupled to HV output circuit 234 suggesting dedicated CV/DVshock electrodes, it is recognized that switching circuitry included inswitch matrix 208 may be used to select any of the available electrodesin a sensing electrode vector, a pacing electrode vector, or a CV/DFshock vector as described previously.

Signals from the electrodes selected for coupling to bandpass amplifier210 are provided to multiplexer 220, and thereafter converted tomulti-bit digital signals by A/D converter 222, for storage in randomaccess memory 226 under control of direct memory access circuit 228 viadata/address bus 218. Microprocessor 224 may employ digital signalanalysis techniques to characterize the digitized signals stored inrandom access memory 226 to recognize and classify the patient's heartrhythm employing any of numerous signal processing methodologies foranalyzing cardiac signals and cardiac event waveforms, e.g., R-waves.One tachyarrhythmia detection system is described in U.S. Pat. No.5,545,186 (Olson et al.), incorporated herein by reference in itsentirety.

ICD 10 or ICD 110 may include a second sensing channel including senseamplifier 204 receiving a V BLANK signal from pace timing and control212 and providing an R OUT signal line 206. In the example shown, asensing electrode vector including electrodes 28 and 30 is coupled toamplifier 200 and a second sensing electrode vector including electrode24 and housing 15 is coupled to the second amplifier 204. Switch matrix208 may select which sensing electrode vector selected from any ofelectrodes 24, 26, 28 and 30 and housing 15 (or electrodes 124, 126, 128130 and 131 and housing 115 in the case of ICD 110) is coupled to eachof the two sensing channels represented by sense amplifiers 200 and 204and which pacing electrode vector is coupled to pace output circuit 216.

It is to be understood that the circuitry shown in FIG. 4 may bemodified according to the particular device requirements. For example,the single chamber ICD 10 of FIG. 1 or extravascular ICD 110 of FIG. 2Amay include one ventricular sense amplifier 200 and terminals forelectrically coupling to electrodes 24, 26, 28 and 30 and/or housing 15(or electrodes 124, 126, 128, 130 or 131 and/or housing 115 in anydesired sensing electrode vector combination.

Upon detection of an arrhythmia, an episode of cardiac signal data,along with sensed intervals and corresponding annotations of sensedevents, may be stored in random access memory 226. The cardiacelectrical signals received via sensing electrode pairs may be stored inRAM 226. In some cases, a near-field and a far-field signal are receivedby the two amplifiers 200 and 204. Typically, a near-field sensingelectrode pair includes a tip electrode and a ring electrode located inthe ventricle, electrodes 28 and 30. A far-field sensing electrode pairincludes electrodes spaced further apart such as any of: thedefibrillation coil electrodes 24 or 26 with housing 15; a tip electrode28 with housing 15; a tip electrode 28 with a defibrillation coilelectrode 24 or 26. The use of near-field and far-field signal detectingarrhythmia episodes is described in U.S. Pat. No. 5,193,535 (Bardy),incorporated herein by reference in its entirety. Annotation of sensedevents, which may be displayed and stored with cardiac signal data, isdescribed in U.S. Pat. 4,374,382 (Markowitz), incorporated herein byreference in its entirety.

The techniques disclosed herein may be applied to one or more cardiacelectrical signals acquired using any combination of the availableelectrodes. In some examples, the sensing circuitry of ICD 10 (or ICD110) includes more than two sensing channels for acquiring more than twocardiac electrical signals. For example, a first cardiac electricalsignal is acquired between the ICD housing 15 and RV coil electrode 24,a second cardiac electrical signal is acquired between the RV coilelectrode 24 and the SVC coil electrode 26, and a third cardiacelectrical signal is acquired between the RV tip electrode 28 and the RVring electrode 30. All three signals may be collected and used bymicroprocessor 224 for analyzing R-waves and RRIs and detecting atrialand/or ventricular arrhythmias. As discussed below in conjunction withFIG. 12, at least two cardiac signals may be stored in RAM 226 when atachyarrhythmia episode is detected for transmission by telemetrycircuit 330 to external device 40. When atrial tachyarrhythmia isdetected, with or without simultaneous detection of ventriculartachyarrhythmia, the two signals may be stored having two different gainsettings to provide two different signals for display on external device40. One signal displayed at a higher gain may result in R-wave clippingbut enables relatively small amplitude P-waves to be more readilyobserved, which enables any relationship between the detected atrial andventricular tachyarrhythmia (if present) to be observed by a clinicianthrough comparison of the two different signals. When ventriculartachyarrhythmia is detected without atrial tachyarrhythmia detection,two signals may be stored both having a gain setting that avoidsclipping of R-waves.

The telemetry circuit 330 includes a transceiver for receiving downlinktelemetry from and sending uplink telemetry to external device 40 usingantenna 332. Telemetry circuit 330 provides bi-directional telemetriccommunication with an external device 40 as described above.

ICD 10 may receive programmable operating parameters and algorithms viatelemetry circuit 330 for storage in RAM 226 and accessed bymicroprocessor 224 for controlling ICD functions. For example, cardiacrhythm detection parameters and therapy control parameters used by ICD10 may be programmed via telemetry circuit 330.

Data stored or acquired by ICD 10, including physiological signals orassociated data derived therefrom, results of device diagnostics, andhistories of detected arrhythmia episodes and delivered therapies, maybe retrieved from ICD 10 by the external device 40 following aninterrogation command received by telemetry circuit 330. Data to beuplinked to the external device and control signals for the telemetrycircuit 330 are provided by microprocessor 224 via address/data bus 218.Received telemetry is provided to microprocessor 224 via multiplexer220. Numerous types of telemetry systems known for use in implantablemedical devices may be implemented in ICD 10.

Other circuitry shown in FIG. 2 is illustrative of therapy deliverycircuitry that may be included in an ICD or other implantable medicaldevice employing the atrial arrhythmia detection technique disclosedherein when the device is configured for providing cardiac pacing,cardioversion and defibrillation therapies. For example, the pacertiming and control circuitry 212 may include programmable digitalcounters which control the basic time intervals associated with varioussingle, dual or multi-chamber pacing modes or anti-tachycardia pacingtherapies delivered in the atria or ventricles. Pacer timing and controlcircuity 212 also sets the amplitude, pulse width, polarity or othercharacteristics of the cardiac pacing pulses under the control ofmicroprocessor 224.

During pacing, escape interval counters within pacer timing and controlcircuitry 212 are reset upon sensing of R-waves or P-waves as indicatedby signals on lines 202 and 206, respectively. In accordance with theselected mode of pacing, pacing pulses are generated by atrial paceoutput circuit 214 and ventricular pace output circuit 216. The paceoutput circuits 214 and 216 are coupled to the desired electrodes forpacing via switch matrix 208. The escape interval counters are resetupon generation of pacing pulses, and thereby control the basic timingof cardiac pacing functions, including anti-tachycardia pacing.

The durations of the escape intervals are determined by microprocessor224 via data/address bus 218. The value of the count present in theescape interval counters when reset by sensed R-waves or P-waves can beused to measure R-R intervals and P-P intervals for detecting theoccurrence of a variety of arrhythmias. Microprocessor 224 may alsotrack the number of pacing pulses delivered, particularly the number ofventricular pacing pulses delivered, during predetermined time periodsas a factor used in classifying the cardiac electrical signal during thetime period.

The microprocessor 224 includes associated read-only memory (ROM) inwhich stored programs controlling the operation of the microprocessor224 reside. A portion of the random access memory (RAM) 226 may beconfigured as a number of recirculating buffers capable of holding aseries of measured intervals for analysis by the microprocessor 224 forpredicting or diagnosing an arrhythmia.

In response to the detection of tachycardia, anti-tachycardia pacingtherapy can be delivered by loading a regimen from microprocessor 224into the pacer timing and control circuitry 212 according to the type oftachycardia detected. In the event that higher voltage cardioversion ordefibrillation pulses are required, microprocessor 224 activates thecardioversion and defibrillation control circuitry 230 to initiatecharging of the high voltage capacitors 246 and 248 via charging circuit236 under the control of high voltage charging control line 240. Thevoltage on the high voltage capacitors is monitored via a voltagecapacitor (VCAP) line 244, which is passed through the multiplexer 220.When the voltage reaches a predetermined value set by microprocessor224, a logic signal is generated on the capacitor full (CF) line 254,terminating charging. The defibrillation or cardioversion pulse isdelivered to the heart under the control of the pacer timing and controlcircuitry 212 by an output circuit 234 via a control bus 238. The outputcircuit 234 determines the electrodes used for delivering thecardioversion or defibrillation pulse and the pulse wave shape.

In some examples, the ICD 10 may be equipped with a patient notificationsystem 250. Any patient notification method known for use in implantablemedical devices may be used such as generating perceivable twitchstimulation or an audible sound. A patient notification system mayinclude an audio transducer that emits audible sounds including voicedstatements or musical tones stored in analog memory and correlated to aprogramming or interrogation operating algorithm or to a warning triggerevent as generally described in U.S. Pat. No. 6,067,473 (Greeninger etal.), incorporated herein by reference in its entirety. In someexamples, ICD 10 provides a response to an atrial tachyarrhythmiadetection by generating a patient notification via system 250 and/or aclinician notification using telemetry circuit 330. An atrialtachyarrhythmia response provided by ICD 10 may include determining anAF burden as the total combined duration of all detected AF episodesduring a predetermined monitoring time interval, e.g., 24 hours, andgenerating a patient notification and/or clinician notification when theAF burden exceeds a threshold.

In the following description, AF detection techniques are described withreference to the circuitry of FIG. 4 of ICD 10 of FIG. 1 or ICD 110 ofFIGS. 2A and 2B. It is to be understood, however, that the methods andtechniques of the descriptions that follow may be implemented in acardiac monitoring device such as the device of FIG. 3 or even anintracardiac pacemaker such as the intracardiac pacemaker 110 of FIGS.2A and 2B, all of which devices may include a microprocessor, memory andsensing circuitry, as generally described in conjunction with FIG. 4,for performing these atrial tachyarrhythmia detection techniques,particularly for detecting AF.

FIG. 5 is a schematic diagram of methods used for detecting AF by amedical device, such as ICD 10, ICD 110. In order to determine whetherAF is occurring, the microprocessor 224 (FIG. 4) may determinedifferences between RRIs based on sensed R-waves (e.g., R OUT signalline 202 in FIG. 4). Microprocessor 224 may make the decision as towhether an AF event is occurring based at least in part on the resultingpattern or signature of RRI differences. As described below, when theresulting signature of RRI differences acquired over a predeterminedtime period indicates AF is occurring, the cardiac signal time period isclassified as AF. AF is detected when a required number of time periodsare classified as AF. Techniques disclosed herein may be utilized aspart of an overall tachyarrhythmia detection and discriminationalgorithm implemented in ICD 10 or ICD 110 or the other devicesdescribed above or in other implantable or external cardiac devices.

The concept of using a signature of RRI differences for detecting AF isillustrated by the generation of a Lorenz scatter plot as shown in FIG.5. Microprocessor 224 determines the differences between consecutivepairs of RR-intervals (δRRs) which can be plotted for a time series ofRRIs. The Lorenz plot 150 is a Cartesian coordinate system defined byδRR_(i) along the x-axis 152 and δRR_(i-1) along the y-axis 154. δRR_(i)is the difference between the i^(th) RRI and the previous RRI,RRI_(i-1). δRR_(i-1) is the difference between RRI_(i-1) and theprevious RRI, RRI_(i-2). As such, each plotted point in a Lorenz plot isdefined by an x-coordinate equaling δRR_(i) and a y-coordinate equalingδRR_(i-1).

Each data point plotted on the Lorenz plot 150 represents an RRI patternrelating to three consecutive RRIs: RRI_(i), RRI_(i-1) and RRI_(i-2),measured between four consecutively sensed R-waves 172. RRI informationis not limited to detection of R-waves and determination of RRIs. Theterms RRI and δRR_(i) as used herein refer generally to a measurement ofventricular cycle length (VCL) and the difference between twoconsecutive VCL measurements, respectively, whether the VCL measurementswere derived from a series of sensed R-waves from a cardiac electricalsignal or a series of ventricular cycle event detections made fromanother physiological signal (e.g., a peak pressure determined from apressure signal). For the sake of illustration, the methods describedherein refer to R-wave detections for performing VCL measurements andthe determination of (δRR_(i), δRR_(i-1)) points.

As illustrated in FIG. 5, a series of R-waves 170 (represented byvertical bars) are sensed and in order to plot a point on the Lorenzplot area 150, a point is determined from the ordered pair (δRR_(i),δRR_(i-1)) by determining successive RRIs determined from the sensedR-waves 170. In the example shown, a first series 172 of threeconsecutive RRIs (RRI_(i-2), RRI_(i-1) and RRI_(i)) provides the firstdata point 155 on the Lorenz plot area 150. δRR_(i-1), which is thedifference between RRI_(i-2) and RRI_(i-1) is near 0. δRR_(i), thedifference between the and RRI_(i-1) and RRI_(i), is a positive change.Accordingly, a (δRR_(i), δRR_(i-1)) point 155 having a y-coordinate near0 and a positive x-coordinate is plotted in the Lorenz plot 150,representing the first series 172 of four sensed R-waves (three RRIs).

The next series 174 of three RRIs provides the next (δRR_(i), δRR_(i-1))point 156 having a negative x-coordinate (the last RRI of series 174being less than the immediately preceding RRI) and a positivey-coordinate (the middle RRI of series 174 being longer than the firstRRI of series). This process of plotting (δRR_(i), δRR_(i-1)) pointscontinues with the three cycle series 176 providing data point 158 andso on.

Illustrative methods and devices for detecting AF using RRI differencesdetermined from a ventricular cardiac electrical signal are generallydescribed in commonly assigned U.S. patent application Ser. Nos.14/520,798, 14/520,938 and 14/520,847 (Cao et al.), all of which areincorporated herein by reference in their entirety. An analysis of aLorenz plot of the successive RRI differences may reveal an RRIvariability pattern that is typical of AF. Other methods for detectingatrial tachyarrhythmias based on the irregularity of ventricular cyclesdetermined from RRI differences that exhibit discriminatory signatureswhen plotted in a Lorenz scatter plot, such as the plot shown in FIG. 5,are generally disclosed by Ritscher et al. in U.S. Pat. No. 7,031,765;Sarkar, et al. in U.S. Pat. Nos. 7,623,911 and 7,537,569; and by Houbenin U.S. Pat. No. 7,627,368, all of which patents are ; incorporatedherein by reference in their entirety.

FIG. 6 is a diagram of a two-dimensional histogram representing a Lorenzplot area 150 used in the techniques disclosed herein for detectingatrial tachyarrhythmia. Generally, the Lorenz plot area 150 shown inFIG. 5 is numerically represented by a two-dimensional histogram 180having predefined ranges 184 and 186 in both positive and negativedirections for the δRR_(i) coordinates (corresponding to x-axis) andδRR_(i-1) coordinates (corresponding to y-axis), respectively. Thetwo-dimensional histogram 180 is divided into bins 188 each having apredefined range of δRR_(i) and δRR_(i-1) values. In one example, thehistogram range might extend from −1200 ms to +1200 ms for both δRR_(i)and δRR_(i-1) values, and the histogram range may be divided into binsextending for a range of 7.5 ms in each of the two dimensions resultingin a 160 bin×160 bin histogram 180. The successive RRI differencesdetermined over a classification time period are used to populate thehistogram 180. Each bin stores a count of the number of (δRR_(i),δRR_(i-1)) data points falling into each respective bin range. The bincounts may then be used by microprocessor 224 in determining RRIvariability metrics and patterns for detecting a cardiac rhythm type.

An RRI variability metric is determined from the histogram bin counts.Generally, the more histogram bins that are occupied, or the more sparsethe distribution of (δRR_(i), δRR_(i-1)) points, the more irregular theVCL is during the data acquisition time period. As such, one metric ofthe RRI variability that can be used for detecting AF, which isassociated with highly irregular VCL, may take into account the numberof histogram bins that have a count of at least one, which is referredto as an “occupied” bin. In one example, an RRI variability metric fordetecting AF, referred to as an AF score, is determined bymicroprocessor 224 as generally described in the above-incorporated '911patent. Briefly, the AF score may be defined by the equation:

AF Score=Irregularity Evidence−Origin Count−PAC Evidence

wherein Irregularity Evidence is the number of occupied histogram binsoutside a Zero Segment 188 defined around the origin of the Lorenz plotarea. During normal sinus rhythm or highly organized atrial tachycardia,nearly all points will fall into the Zero Segment 188 because ofrelatively small, consistent differences between consecutive RRIs. Ahigh number of occupied histogram bins outside the Zero segment 188 istherefore positive evidence for AF.

The Origin Count is the number of points in the Zero Segment 188 definedaround the Lorenz plot origin. A high Origin Count indicates regularRRIs, a negative indicator of AF, and is therefore subtracted from theIrregularity Evidence term. In addition, a regular PAC evidence scoremay be computed as generally described in the above-incorporated '911patent. The regular PAC evidence score is computed based on a clustersignature pattern of data points that is particularly associated withpremature atrial contractions (PACs) that occur at regular couplingintervals and present regular patterns of RRIs, e.g., associated withbigeminy (short-short-long RRIs) or trigeminy (short-short-short-longRRIs). In other embodiments, the AF score and/or other RRI variabilityscore for classifying an atrial rhythm may be determined bymicroprocessor 224 as described in any of the above-incorporated '765,'316, '911, '569 and '368 patents. Methods for rejecting noise indetermining Lorenz plot points and an AF score are generally disclosedin U.S. Pat. No. 8, 639,316 (Sarkar, et al.), incorporated herein byreference in its entirety. Methods for adjusting the AF score based onthe presence of ectopy may be used in the techniques disclosed hereinand are generally disclosed in U.S. Pat. No. 8,977,350 (Sarkar, et al.),incorporated herein by reference in its entirety. Other techniques thatmay be used in computing an AF score are generally disclosed in U.S.patent application Ser. Nos. 14/695,135, 14/695,156, 14/695,171 and14/695,111 (Sarkar, et al.), all filed on Apr. 24, 2015 and incorporatedherein by reference in their entirety.

The AF score is compared to an AF score threshold for classifying apredetermined time period of a cardiac signal as AF or non-AF based onthe RRI analysis. The AF score threshold may be selected and optimizedbased on historical clinical data of selected patient populations orhistorical individual patient data, and the optimal AF score thresholdsetting may vary from patient to patient. In an illustrative example,the AF score may have a possible range of 0 to 100. The AF scorethreshold may be set between 25 and 75. If the AF score meets or crossesan AF score threshold, the time period over which the RRIs werecollected, and thus the cardiac signal occurring within the time period,is classified as an AF time period. The AF score threshold may beadjusted after classifying at least one time period of the cardiacsignal as being AF and the adjusted AF score threshold may be used forclassifying subsequent time periods, which may lead to an AF detection.The adjusted AF score threshold is less than the initial AF scorethreshold and may have a value ranging from 19 to 57 in the examplegiven above where the maximum AF score is 100 and the initial AF scorethreshold is at least 26 and not more than 75. Thus, the adjusted AFscore threshold may be between 65-85% of the initial AF score thresholdand, in some instances between 70-75% of the initial AF score.

An AF detection is made when a threshold number of detection timeperiods are classified as AF. In one example, a single n-second orn-minute time period classified as AF based on the AF score meeting theAF score threshold may result in an AF detection. In other examples, ahigher number of time periods, e.g., three two-minute time periods for atotal of 6 minutes of the cardiac electrical signal, may be required tobe classified as being AF before detecting the heart rhythm as AF. Asdescribed below in conjunction with FIGS. 13-15, the threshold number ofAF classified time periods required to detect AF may be automaticallyadjusted by microprocessor 224 based on the history of AF episodesdetected in a given patient.

The microprocessor 224 provides a response to the AF detection, whichmay include withholding, adjusting or delivering a therapy (e.g.,withholding ATP or shock therapy for treating a ventriculartachyarrhythmia or delivering an atrial anti-tachyarrhythmia therapy ifavailable), storing cardiac signal data that can be later retrieved by aclinician using external device 40, triggering patient notificationsystem 250, transmitting data via telemetry circuit 330 to alert aclinician, patient or caregiver, and/or triggering other signalacquisition or analysis.

The RRI analysis may continue to be performed by microprocessor 224after an AF detection is made to fill the histogram during the nextdetection time period. After each detection time period, the AF scoremay be re-determined and the histogram bins are re-initialized to zerofor the next detection time period. The new AF score (or other RRIvariability metrics) determined at the end of each detection time periodmay be used to determine if the AF episode is sustained or terminatedafter the initial AF detection is made.

FIG. 7 is a flowchart 300 of a method for determining a factor forclassifying time periods for detecting atrial arrhythmias according toone example. Flow chart 300 and other flow charts presented herein areintended to illustrate the functional operation of ICD 10 or anotherdevice performing the disclosed methods, and should not be construed asreflective of a specific form of software, firmware or hardwarenecessary to practice the methods. It is believed that the particularform of software, firmware and/or hardware will be determined primarilyby the particular system architecture employed in the device and by theparticular detection and therapy delivery methodologies employed by thedevice. Providing software, firmware and/or hardware to accomplish thetechniques disclosed herein in the context of any modern medical device,given the disclosure herein, is within the abilities of one of skill inthe art.

Methods described in conjunction with flow charts presented herein maybe implemented in a non-transitory computer-readable medium thatincludes instructions for causing a programmable processor, such asmicroprocessor 224, to carry out the methods described. A“computer-readable medium” includes but is not limited to any volatileor non-volatile media, such as a RAM, ROM, CD-ROM, NVRAM, EEPROM, flashmemory, and the like. The instructions may be implemented as one or moresoftware modules, which may be executed by themselves or in combinationwith other software.

As illustrated in FIG. 7, the microprocessor 224 identifies ventricularevents at block 301, such as R-waves based on Rout signal line 202, andidentifies the ventricular event as being either an intrinsic sensedevent Vs or a paced event Vp resulting from pacing being delivered byICD 10 or 10′ (or by ICD 110 or pacemaker 101). Depending upon thenumber of RR intervals chosen for determining RR interval differences,microprocessor 224 determines whether a predetermined number of events,either a ventricular pacing event Vp or intrinsic ventricular sensedevent VS, have been identified at block 302. For example, according toone example, if the desired number of RR intervals for determiningsuccessive RR interval differences is three, the predetermined number ofevents utilized in block 302 would be four events, with the four eventsforming an event window. If the predetermined number of events has notbeen reached, “No” branch of block 302, microprocessor 224 determinesthe next ventricular event, at block 301, and the process is repeated.

Once the predetermined number of events are identified, “Yes” branch ofblock 302, an event window is identified based on the four events, atblock 304, and a determination may be made made as to whether the numberof the events in the event window that are ventricular pace Vp events isless than or equal to a predetermined pacing event threshold at block306. For example, according to one example, the pacing event thresholdis set as one so that microprocessor 224 determines whether one or lessof the identified events in the event window are ventricular paceevents. If the number of identified events in the event window that areventricular pace Vp events is not less than or equal to, i.e., isgreater than, the predetermined pacing event threshold, “No” branch ofblock 306, microprocessor 224 identifies the next event at block 301,and the process is repeated.

If the number of events in the event window that are ventricular pace Vpevents is less than or equal to the predetermined pacing eventthreshold, “Yes” branch of block 306, microprocessor 224 determineswhether each of the RR intervals associated with the events in thecurrent event window are greater than a predetermined interval thresholdat block 308. For example, according to one example, microprocessor 224determines whether each of the RR intervals associated with the eventsin the event window is greater than 220 milliseconds. If each of the RRintervals associated with the events in the event window are not greaterthan the predetermined interval threshold, “No” branch of block 308,microprocessor 224 identifies the next event at block 301, and theprocess is repeated using the next identified event and the resultingnext event window.

If each of the RRIs associated with the events in the event window aregreater than the predetermined interval threshold, “Yes” branch of block308, microprocessor 224 determines differences between successive RRIsassociated with the identified events in the event window, block 310.Once the RRI differences for the current event window have beendetermined at block 308, to populate a Lorenz plot histogram asdescribed above, microprocessor 224 determines whether a predeterminedtime period has expired at block 312. Microprocessor 224 may set a timeror counter to control acquisition of RRI differences over apredetermined time period at the onset of the method of flow chart 300.In one example, the predetermined time period may be set to two minutes.If the time period has not expired, “No” branch of block 312,microprocessor 224 returns to block 301 to identify the next ventricularevent and the process is repeated using the next event and the resultingnext event window.

Once the timer has expired, “Yes” branch of block 312, microprocessor224 determines an AF score at block 314, based on the determined RRIdifferences during the predetermined time period, e.g., two minutes. TheAF score may be determined as described above with respect to FIG. 6and/or the incorporated patents. As described below in conjunction withFIG. 8, the determined AF score for the predetermined time period isused to classify the time period (and thus the cardiac signal during thetime period) as an AF time period, a non-AF time period or anunclassified time period. The stored RRI differences are then clearedand all counters and timers reset at block 316. A timer set to thepredetermined time period, e.g., two minutes, is reset. Microprocessor224 identifies the next ventricular event at block 300, and the processis repeated for the next time period using the next identified eventsand the next event windows.

FIG. 8 is a flowchart 400 of a method for classifying a predeterminedtime period according to one example. The example described in flowchart400 of FIG. 7 will be described in the context of having predeterminedtime periods that are two minutes in length. However, the techniquesdescribed in FIG. 7 or elsewhere throughout this description can be forpredetermined time periods that are longer or shorter than two minutes.Once the predetermined time period, e.g., a two-minute time period, hasexpired and a Lorenz plot has been populated with a point associatedwith ordered pairs representing each determined RR interval differencedetermined based on the intervals in each event window occurring duringthe two-minute time period as described in conjunction with FIGS. 5, 6and 7, microprocessor 224 determines whether to classify the time periodas being either an AF time period, a non-AF time period, or anunclassified time period (i.e., the time period can neither beclassified as an AF time period nor a non-AF time period). For example,microprocessor 224 may analyze one or more of several factors, in anycombination or particular order, to make the determination.

As described in conjunction with the example of FIG. 8, among thefactors that may be analyzed for classifying the two-minute time periodare the number of valid RRI difference pairs, RRI lengths, number ofpaced beats, number of short intervals, presence of oversensing ofventricular events, presence of T-wave oversensing, detection of aventricular tachyarrhythmia (e.g., SVT, VT or VF or more generallyreferred to as “other episodes”), and the AF score. However,microprocessor 224 may analyze only a subset of these factors and/orinclude other factors.

Microprocessor 224 may determine the number of RRI difference pairsacquired during the two-minute time period at block 401, where each RRIdifference pair represents one point of the Lorenz plot. A determinationis then made as to whether the total number of RRI difference pairsformed during the two-minute time period is greater than an intervalpair threshold at block 402. According to one example, a thresholdnumber of RRI difference pairs is set at 30, though other thresholds maybe used. If the total number of RRI difference pairs (representing threeconsecutive RRIs) during the two-minute time period is less than thethreshold, “Yes” branch at block 402, the two-minute time period isdetermined to be unclassified at block 404. In the example describedabove in which the threshold is set at 30, the “Yes” branch of block 402means that less than 30 RRI difference pairs were determined during thetwo-minute time period, resulting in the Lorenz plot histogram beingpopulated with less than 30 points. An AF score determined from fewerthan the threshold number of RRI difference pairs may not yield areliable AF score for the predetermined time period and therefore is notused to classify the time period as either AF or non-AF.

If the number of RRI difference pairs that are formed during thetwo-minute time period is not less than the interval pair threshold (30in the example above), “No” branch of block 402, the interval pairsfactor for classifying the time period as either AF or non-AF based onan AF score determined from the RRI difference pairs is satisfied. Inother words, using the example above, 30 or RRI difference pairs weredetermined during the two-minute time period, resulting in the Lorenzplot histogram being populated with 30 or more points. The number of RRIdifference pairs obtained during the pre-determined time period isadequate to reliably classify the time period as AF or non-AF based onthe AF score.

According to another example, microprocessor 224 may additionally oralternatively determine, at block 410, the total number of RRIs duringthe predetermined time period that were determined to be less than theinterval threshold applied at block 308 of flow chart 300. If more thana threshold number of RRIs, e.g., more than a predetermined number ofRRIs or a predetermined percentage of the total number of RRIs occurringduring the two-minute time period, are less than the interval threshold,“Yes” branch at block 412, the two-minute time period is determined tobe unclassified, at block 404. If the number of RRIs less than theinterval threshold does not reach or exceed a predetermined number,e.g., if less than 10 RRIs are less than the interval threshold duringthe two-minute time period, this RRI length factor is determined not tobe satisfied at block 412 (“No” branch of block 412) for classifying thepredetermined time interval as unclassified. Based on at least thisfactor, a classification of either AF or non-AF based on the AF score iswarranted.

In order to classify the two-minute time period as either AF or non-AF,microprocessor 224 may determine, at block 414, a short interval countof the total number of RRIs from all of the event windows obtainedduring the two-minute time period that were less than or equal to apredetermined short interval threshold, such as 120 milliseconds or 130milliseconds, for example. Microprocessor 224 determines whether theshort interval count is greater than a short interval threshold, atblock 416, such as 5 short intervals for example. Too many shortintervals during the two-minute time period indicates the possibility ofventricular oversensing of non-physiological signals such as EMI or leadnoise due to lead fracture. In this situation, the RRIs may beunreliable for determining an AF score and classifying the time periodas AF or non-AF based on the AF score.

If the determined short interval count is greater than the shortinterval count threshold, “Yes” branch at block 416, the two-minute timeperiod is determined to be unclassified at block 404. On the other hand,if the short interval count is less than the short interval countthreshold, the time period can be classified based on the AF score, “No”branch at block 416. This short interval count factor minimizes false AFdetection due to lead noise oversensing.

Microprocessor 224 may additionally or alternatively determine thenumber of events identified during the total two-minute time periodwithin all of the event windows that were determined to be ventricularpace Vp events at block 418. A determination is made as to whether thedetermined number of ventricular pace Vp events identified during allevent windows of the two-minute time period is greater than a totalventricular pace Vp event threshold at block 420. According to oneexample, the total ventricular pace Vp threshold is set as 30ventricular pace Vp events, though other thresholds may be used.

If the number of ventricular pace Vp events during the two-minute timeperiod is greater than the total ventricular pace Vp event threshold,“Yes” branch of block 420, microprocessor 224 classifies the two-minutetime period as unclassified at block 404. Ventricular pacing pulses mayinclude bradycardia pacing pulses and/or ATP pacing pulses and may bedelivered by ICD 10 or 110 or by another implanted device, e.g.,pacemaker 110. On the other hand, if the determined number ofventricular pace Vp events is not greater than Vp event threshold, “No”branch at block 420, the two-minute time period is not classified asunclassified; a classification of AF or non-AF based on the AF score maybe made as long as no other factors lead to a determination of the timeperiod being unclassified.

Microprocessor 224 may be configured to simultaneously evaluate R-wavesand RRIs for detecting supraventricular tachycardia (SVT), VT and VFwhile the AF detection algorithms described herein are operating. ICD 10may be configured to deliver therapies such as ATP in response todetecting VT. As such, if a ventricular tachyarrhythmia detection, e.g.,SVT, VT or VF detection, is being made during or at the expiration ofthe current time period, as determined at block 421, the current timeperiod is determined to be unclassified at block 404. If no otherepisode detections are being made, the process may advance to block 422.

The microprocessor 224 may additionally or alternatively determinewhether ventricular event oversensing caused by noise was detectedduring the two-minute time period, at block 422. Detection ofoversensing may be performed by microprocessor 224 using an implementedoversensing detection scheme, such as the oversensing detection methodsgenerally described in U.S. Pat. No. 7,333,855 to Gunderson et. al.,incorporated herein by reference in its entirety. If oversensingdetection criteria were met or were in the process of being met duringthe two-minute time period, “Yes” branch of block 422, the two-minutetime period is determined to be unclassified at block 404. Detection ofoversensing indicates that the RRIs may be unreliable for determining anAF score and classifying the time period based on the AF score. If adetection of oversensing was not made or not in the process of beingmade during the two-minute time period, “No” branch of block 422, an AFor non-AF classification may be made based on the AF score as long asother factors do not lead to the time period be classified asunclassified.

Microprocessor 224 may determine whether T-wave oversensing occurredduring the two-minute time period at block 424. The determination ofT-wave oversensing may be performed by ICD 10 using an implementedT-wave oversensing detection scheme, such as the T-wave oversensingdetermination described in U.S. Pat. No. 7,831,304 (Cao, et al.),incorporated herein by reference in its entirety. If a determination ofT-wave oversensing was made or was in process during the two-minute timeperiod, “Yes” branch of block 424, the T-wave oversensing factor issatisfied as an indication of the two-minute time period beingunclassified. Microprocessor 224 classifies the two-minute time periodas unclassified at block 404. If a determination of T-wave oversensingwas not made or was not in the process of being made during thetwo-minute time period, “No” branch of block 424, the T-wave oversensingfactor is not satisfied. Microprocessor 224 advances to block 426 toclassify the time period based on the AF score.

In this way, ICD 10 or ICD 110 may analyze the cardiac electrical signalover the two-minute time period for one or more of the describedfactors, which if satisfied would cause the two-minute time period to beclassified as “unclassified.” In other words, ICD 10 or 110 may analyzeall of the described factors or only a subset of the described factorsin making this determination. In some examples, if at least one thedescribed factors for identifying the two-minute time period as beingunclassified is met, the two-minute time period is classified asunclassified at block 404. If none of the factors evaluated in blocks401 through 424 are determined to be satisfied according topredetermined criteria, the time period is classified as either AF ornon-AF based on the AF score. As such, the AF score is determined basedon the populated Lorenz plot histogram as described above. If the AFscore is greater than an AF threshold at block 426, the two-minute timeperiod is classified as AF at block 406. On the other hand, if the AFscore is not greater than the AF threshold, “No” branch of block 426,the two-minute time period is classified as a non-AF at block 408.

It is understood that the determination of whether the time period isclassified as unclassified (block 404), classified as AF (block 406), orclassified as non-AF (block 408), may be made in any order, or at thesame time, so that the determination of the two-minute time period asbeing an unclassified time period may be used to override an initialdetermination of the two-minute time period as being classified as AF ornon-AF, or be made prior to determining the AF score for making aclassification based on the AF score.

FIG. 9 is a schematic diagram of atrial fibrillation detection that maybe performed by a medical device according to one example. The examplesdescribed in FIG. 9 will be described in the context of classifyingpredetermined time periods that are two minutes in length. However, thetechniques described in FIG. 9 can be implemented by classifyingpredetermined time periods that are longer or shorter than two minutes.

As illustrated in FIG. 9, the microprocessor 224 classifies the cardiacsignal of each two-minute time period as being either AF, non- AF orunclassified using the method described in conjunction with FIG. 7. Theclassifications of the time periods are used to detect an AF episode.For example, once a predetermined number of two-minute time periods,such as three time periods, have been classified as AF, the devicedetects the AF episode. Therefore, as illustrated in the scenario oftiming diagram (a) of FIG. 8, once the predetermined number oftwo-minute time periods, 500, 502 and 504, are classified as AF,microprocessor 224 detects the AF episode at time 505. Themicroprocessor 224 may track the number of two-minute time periodsclassified as AF by updating an AF event counter each time a time periodis classified as AF.

However, in the scenario illustrated in timing diagram (b), twoconsecutive two-minute time periods 506 and 508 are classified as beingAF, but the next two-minute time period 510 is determined to beunclassified, followed by a subsequent time period 512 being classifiedas AF. According to one example, microprocessor 224 may ignore theunclassified two-minute time period 510 and detect an AF episode at time513 once the third time period 512 is classified as AF, so that an AFepisode may be detected despite one or more unclassified time periodsoccurring between time periods classified as AF.

In the timing diagram of scenario (b), at the identification oftwo-minute time period 506, an AF event counter may be incremented toone. At the identification of subsequent two minute period 508, the AFevent counter is incremented to two. At the classification of subsequenttwo-minute time period 510, since the cardiac signal was determined tobe unclassified, the AF event counter remains at a count of two. At theclassification of subsequent two-minute time period 512, the AF eventcounter is incremented to three, and an AF episode is detected inresponse to the AF event counter reaching the AF detection threshold,which is 3 in this example.

As illustrated in the timing diagram of scenario (c), the classificationof one or more time periods as non-AF result in no detection of an AFepisode. During the determination of whether the predetermined number oftwo-minute time periods are classified as AF, the microprocessor 224updates the AF event counter each time an AF classification is made asdescribed above. For example, upon classification of two-minute timeperiod 514, the AF event counter is incremented to one, and at theclassification of subsequent two-minute time period 516, the AF eventcounter is incremented to two. If two-minute time period 518 were alsoclassified as AF, microprocessor 224 would detect an AF episode, sincethree two-minute time periods classified as AF would have occurred,e.g., as described in the timing diagram of scenario (a) above. However,since two-minute time period 518 is classified as non-AF, an AF episodedetection is not made. The non-AF classification of time period 518 maybe evidence that an AF episode causing AF classifications of timeperiods 514 and 516 is terminated or a non-sustained AF episode. Inresponse to classifying time period 518 as non-AF, the AF event counteris reset to zero. In other examples, the AF counter may be decreasedwhen a time period is classified as non-AF rather than immediately resetto zero.

In the timing diagram of scenario (d), at the classification oftwo-minute time period 522 as being AF, the AF event counter isincremented to one, and at the classification of subsequent two-minutetime period 524 as AF, the AF event counter is incremented to two. Atthe classifications of subsequent two-minute time periods 526 and 528,both determined to be unclassified, the AF event counter remainsunchanged at a count of two. Upon classification of subsequenttwo-minute time period 530 as being AF, the AF event counter isincreased to three, and an AF episode is detected at time 531.

Had any of time periods 524, 526, 528 or 530 been classified as non-AF,the AF event counter would have been reset to zero, and the processrepeated starting with the next classified two-minute time period.However, in addition to resetting the AF event counter in response to atwo-minute time period being classified as a non-AF time period,microprocessor 224 may also be configured to reset the AF event counterto zero if a predetermined number of two-minute time periods aredetermined to be unclassified. For example, five consecutive two-minutetime periods determined to be unclassified may cause the AF eventcounter to be reset to zero. In other examples, more than five or fewerthan five unclassified time periods, which may not be required to beconsecutive, may cause the AF counter to be decremented or reset tozero. Therefore, in the timing diagram of scenario (e), at theidentification of two-minute time period 532 as AF, the AF event counteris incremented to one. At the identification of subsequent two-minutetime period 534 as AF, the AF event counter is incremented to two. Atthe identification of the four subsequent two-minute time periods 536,538, 540 and 542, all determined to be unclassified, the AF event countremains unchanged at two. In the example shown, the next two-minute timeperiod 546 is classified as AF. The AF event counter is incremented fromtwo to three, and an AF episode is detected at 545 by microprocessor 224in response to the AF event counter reaching the threshold count, whichis three in this example.

On the other hand, if the subsequent two-minute time period 546 had beendetermined to be unclassified, the AF event counter would be reset tozero in response to a threshold number (five in this example) ofconsecutive unclassified time periods. If time period 546 had beenclassified as a non-AF time period, the AF event counter would also bereset to zero. In either of these two cases, if the time periods 532 and534 represent a true AF episode, the AF episode has terminated or isnon-sustained as evidenced by the unclassified and/or non-AF classifiedtime periods. The process is repeated starting with the next classifiedtwo minute interval.

FIG. 10 is a schematic diagram of a method for detecting atrialfibrillation that may be performed by ICD 10 or ICD 110 (or cardiacmonitoring device 60) according to another example. The examplesdescribed in FIG. 10 will be described in the context of havingpredetermined time periods that are two minutes in length and an AFdetection threshold set equal to 3 time periods classified as AF.However, the techniques described may utilize different time perioddurations and/or different thresholds. As described below in conjunctionwith FIGS. 13-15, the threshold number of time periods, or total timeduration of the cardiac signal required to be classified as AF may beautomatically adjusted by microprocessor 224.

The microprocessor 224 classifies the cardiac signal within eachtwo-minute time period as being either AF, non- AF or unclassified usingthe method described in conjunction with FIG. 8. If factors that causethe two-minute time period to be unclassified are not satisfied, eachtwo-minute time period is classified as AF or non-AF based on the AFscore. In the method of FIG. 10, the threshold that the AF score iscompared to for classifying a time period is not a fixed value but isdynamically adjusted by microprocessor 224 in response toclassifications of two-minute time periods.

For example, once a predetermined number of time periods, such as onetime period, has been classified as AF based on a first AF scorethreshold value, if the next predetermined number of time periods areclassified as any combination of AF and/or unclassified, the AF scorethreshold is adjusted to a second, lower value. In other words,following an initial AF classification using the first, higher AF scorethreshold, microprocessor 224 decreases the AF score threshold to thesecond lower value at the expiration of a predetermined number of nextconsecutive time periods, e.g., two consecutive time periods followingthe initial AF classification in the examples illustrated in FIG. 9, aslong as none of the predetermined number of next consecutive timeperiods are classified as non-AF. In other instances, the predeterminednumber of next consecutive time periods may be less than two, e.g., zeroor one, or more than two. If any of the predetermined number of nextconsecutive time periods following an initial AF classification areclassified as non-AF, the AF score threshold remains at the first higherthreshold value.

Therefore, as illustrated in the scenario of timing diagram (a) of FIG.10, an initial time period 610 is classified as AF based on the AF scoredetermined for time period 610 being greater than a first AF scorethreshold 602 and analysis of other classification factors does not leadto an unclassified time period (as described with FIG. 8). The first AFscore threshold 602 stays in effect for at least two more consecutivetime periods 612 and 614 in this example. If both of these time periodsare also classified as AF, in response to an AF score exceeding thefirst AF score threshold 602, AF is detected at time 622. Additionally,microprocessor 224 adjusts the AF score threshold to a second, lower AFscore threshold 604 at time 622. The AF score of subsequent time periodswill be compared to this lower threshold 604 for classifying therespective time periods.

The lower AF score threshold 604 may be set to a percentage of theinitial AF score threshold 602, e.g., approximately 75% of the initialAF score. To illustrate, when the maximum possible value of the AF scoreis 100, the first AF score threshold may be set at 75 and adjusted to asecond, lower AF score of 57. In another example, the first AF scorethreshold is 60 and the second is 45. In still other examples, the firstAF score threshold is 60 and the second is 45, the first is 50 and thesecond is 38, the first is 40 and the second is 30, or the first is 25and the second is 19. A user may program the AF score thresholds basedon selection of a least sensitive, e.g., first threshold of 75 andsecond threshold of 57, to most sensitive, e.g., first threshold 25 andsecond threshold 19, with the other example given above corresponding toa less sensitive setting (first threshold 60 and second threshold 45),balanced sensitivity (first threshold 50 and second threshold 38), andmore sensitivity (first threshold 40 and second threshold 30). In otherexamples, the actual values of the first and second thresholds may beprogrammable selected individually in any combination of a first range,e.g., from 25 to and including 75 for the first threshold, and a secondrange, e.g., from 19 to and including 57 for the second threshold, aslong as the first threshold is greater than the second threshold value.In other examples, the second threshold may be set to be anotherpercentage of the initial threshold, e.g., between 65-85%, 70-80%, orsome other percentage.

By reducing the AF score for subsequent time periods, AF detectionsensitivity is increased at appropriate times. AF detection specificityis maintained by using the first higher AF score threshold and applyingthe factors that lead to unclassified time periods. For example, thenext two consecutive time periods 616 and 618 are both classified as AFbased on an AF score exceeding the second threshold 604, even though thefirst, higher threshold 602 is not met (and factors leading to anunclassified classification are not present). The AF episode is detectedas still being in progress during time periods 616 and 618 even thoughthe AF scores for these time periods 616 and 618 are each less than thefirst threshold 602. The next time period 620 is classified as non-AFdue to an AF score being less than the second threshold 604. In responseto the non-AF classification, microprocessor 224 adjusts the AF scorethreshold from the lower threshold 604 back to the higher threshold 602at time 624. Termination of the AF episode is detected in response tothe non-AF classification. The AF episode duration 615 is the timeinterval from the start of the earliest time period 610 classified as AFthat led to AF detection at time 622 to the end of last AFclassification time period 618 that precedes termination detection attime 624, i.e., that precedes the time period 620 classified as non-AF.

In the scenario illustrated in timing diagram (b), two consecutivetwo-minute time periods 632 and 634 are determined to be unclassifiedafter an initial time period 630 that is classified as AF based on thefirst AF score threshold 602. In response to neither of the two timeperiods 632 and 634 being classified as non-AF following the initial AFclassification of time period 630, microprocessor 224 adjusts the AFscore threshold at time 642 to the second lower threshold 604. Threeconsecutive classifications including at least an initial AFclassification and no non-AF classifications cause an adjustment of theAF score threshold. As such, in one example, time periods 632 and 634immediately and consecutively following the initial AF classified timeperiod 630 may both be unclassified (as shown in this example), both beclassified as AF, or one classified as AF and one unclassified to causethe AF score threshold to be adjusted at time 642.

Since only one time period 630 has been classified as AF in the exampleshown, however, an AF detection is not made at time 642 when the AFscore threshold is adjusted. The next two time periods 636 and 638 areclassified as AF in response to an AF score being greater than theadjusted AF score threshold 604 (and factors that would cause anunclassified classification to be made not being identified). When theAF event counter reaches a count of three at time 643, an AF detectionis made. The next time period 640 is classified as non-AF in thisexample. Termination of the AF episode is detected, and the AF scorethreshold is adjusted from the lower value 604 back up to the highervalue 602 at time 644 in response to the non-AF classification andresulting episode termination detection.

The episode duration 635 starts with the earliest time period 630 thatwas classified as AF and led to AF detection at time 643 and extendsthrough the latest AF-classified time period 638 prior to terminationdetection at time 644. The episode duration 635 includes unclassifiedtime periods 632 and 634 that do not lead to detection of termination attime 644. Unclassified time periods 632 and 634 occur betweenAF-classified time periods 630 and 636 and are therefore included in AFepisode duration 635. The time periods 632 and 634 may be classified asunclassified due to any of the other factors described in FIG. 8. In oneparticular example, one or both of the time periods 632 and 634 may beunclassified due to ventricular tachyarrhythmia detection (block 421 ofFIG. 8). By allowing time periods 632 and 634 to be classified asunclassified when ventricular tachyarrhythmia is being detected, thedetection of AF and determination of the AF episode duration 635 areuninterrupted. The detection of an AF episode that is concurrent with aventricular tachyarrhythmia episode provides important diagnosticinformation for the clinician to use in properly determining thepatient's heart rhythm status and subsequent treatment.

In scenario (b) and other scenarios that follow, the time periodsdetermined to be unclassified, e.g., time periods 632 and 634 arerepresented as having AF scores being equal to the currently set AFscore threshold. It is to be understood, however, that an actual AFscore, if determined, may be greater than, equal to, or less than thecurrent value of the AF score threshold but is not used to classify thetime period when the analysis of other factors cause the time period tobe determined as unclassified as described in conjunction with FIG. 8.In some cases, if the time period is determined to be unclassified dueto analysis of one or more factors as described in conjunction with FIG.8, determination of an AF score for the current time period may not bemade; classification of the time period as unclassified may preclude theneed to determine the AF score in some examples.

In scenario (c), the AF score threshold is adjusted from a firstthreshold 602 to a second threshold 604 at time 674 after an initial AFclassified time period 650 based on the first, higher threshold 602followed by two consecutive time periods 652 and 654 that do not includea non-AF classification. Microprocessor 224 may increment an AF eventcounter in response to each AF classification and increment anunclassified event counter in response to each unclassified time period.Accordingly, in the example of scenario (c), at time 674 the AF eventcounter is at a count of one, and the unclassified event counter is at acount of two. After time period 656, the unclassified event counter isat a count of three, and after time period 658 the unclassified eventcounter is at a count of four. The next two time periods 670 and 672 areclassified as AF based on the respective AF scores exceeding the second,lower AF score threshold 604. If the next time period 670 is also anunclassified time period, such that five unclassified time periods occurconsecutively, the AF event counter and the unclassified event countermay be reset to zero, and the AF score threshold may be increased to thefirst, higher AF score threshold 602. Microprocessor 224 may thereforeadjust the AF score threshold and reset counters in response todetecting a predetermined number of consecutive unclassified timeperiods.

In the example shown, the next time period 670 is classified as AF sothe unclassified event counter remains at a count of four. The AF eventcounter is increased to two after time period 670 and to three aftertime period 672. AF is detected at time 676 in response to the AF eventcount reaching the detection threshold, which is three in this example.The AF score threshold remains at the second, lower threshold 604 untiltermination of the AF episode is detected in response to a non-AFclassification, e.g., time period 675, or a predetermined number ofconsecutive unclassified time periods, e.g., five consecutiveunclassified time periods. At time 678, the AF score threshold isadjusted to the first, higher threshold 602 in response to the non-AFclassification of time period 675. As shown by the example of scenarios(b) and (c), an AF episode may be detected after the AF threshold isadjusted to the second, lower threshold.

The episode duration 655 in scenario (c) begins with AF time period 650and extends through AF time period 672 which led to AF detection at time676. This episode duration 655 includes the consecutive unclassifiedtime periods 652, 654, 656, and 658 which do not lead to detection of AFtermination at 678.

Scenario (d) shows another example of a series of two-minute time periodclassifications and the corresponding adjustment to the AF scorethreshold. An initial time period 680 is classified as AF based on thefirst, higher AF score threshold 602. The AF event counter is increasedto a count of one. The next time period 682 is classified as non-AFbased on the first AF score threshold 604. The AF event counter may bereset to zero in response to the non-AF classification. The unclassifiedtime period 684 may not be counted by microprocessor 224 since the AFevent counter is currently zero.

A subsequent sequence of AF-U-AF (time periods 686, 688 and 690,respectively) result in an AF event count of two and an unclassifiedevent count of one. The two consecutive time periods 688 and 690,following the AF time period 686 and classified as unclassified and AF,respectively, result in a combined event count of the AF andunclassified time periods being equal to three. In response to thiscombined event count of three, microprocessor 224 adjusts the AF scorethreshold from the first, higher AF score threshold 602 to the secondlower AF score threshold 604 at time 695. AF is not yet detected becausethe AF event count is two. The next time period 692 is classified as AFbased on a comparison of the AF score to the second, lower AF scorethreshold 604. Microprocessor 224 increases the AF event count to threeand detects AF at time 697 in response to the AF event count reachingthe detection threshold. Upon detecting AF at time 697, the unclassifiedevent counter is reset to zero. The unclassified event counter willcount unclassified time segments beginning from zero after the AFdetection in order to count consecutive unclassified time periods fordetecting termination of the AF episode. The unclassified event countreaches two after time periods 694 and 696. The next time period 698 isclassified as non-AF resulting in detecting termination of the AFepisode at time 699. All event counters are reset to zero, and the AFscore threshold is adjusted back to the first, higher threshold 602 attime 699.

The episode duration 685 starts with AF-classified time period 686 whichis the earliest AF classified episode that led to AF detection at time697. The episode duration includes unclassified time period 688 whichdid not contribute to detection of termination at block 699. Episodeduration 685 ends with the last AF-classified time period 692 prior todetecting termination at time 699. Unclassified time periods 694 and 696may, in some instances, not be included in the episode duration 685because they immediately precede the non-AF classified time period 698that results in episode termination detection with no interveningAF-classified episode. In other instances, however, those unclassifiedtime periods may also be included in the episode duration 685.

The first and second AF score thresholds 602 and 604 may be fixed valuesor may be programmable by a user. In one example, a user may program thefirst and second AF score thresholds 602 and 604 to be increased or setto relatively higher respective values than currently programmed valuesor decreased or set to relatively lower values than the currentlyprogrammed values. Both the first and second AF score thresholds areadjusted together up or down by the same increment or decrementrespectively, in response to the user-entered programming command. Inother examples, a user may programmably select each of the first andsecond AF score thresholds tailored to individual patient need.

While only two different AF score thresholds 602 and 604 are illustratedin the example of FIG. 10, it is understood that the AF score thresholdmay be adjusted between three or more AF score threshold values in otherexamples. For instance, after AF detection is made at time 697, the AFscore threshold set to the second, lower threshold 604 could be reducedto a third lowest AF score threshold to allow continuing detection ofthe AF episode using less stringent criteria than the initial AFdetection criteria. In other examples, once the AF detection is made attime 697, the AF score threshold could be increased from the second,lower threshold 604 back up to the first, higher threshold 602 or to athird, intermediate threshold value between the second, lower threshold604 and the first, higher threshold 602. The third intermediatethreshold value may be applied for classifying subsequent time periodsuntil termination of the AF episode is detected based on a predeterminednumber of time periods being classified as non-AF based on an AF scorefalling below the third intermediate threshold value.

In the example scenarios of FIG. 10, the AF score threshold is adjustedafter at least two consecutive time period classifications of anycombination of AF and unclassified immediately follow a preceding orinitial AF classified time period. In other examples, the AF scorethreshold may be adjusted after fewer or more time periods. For example,a single time period classified as AF may cause the AF score thresholdto be reduced to a second lower value. In other examples, at least oneunclassified or AF time period following an immediately preceding AFtime period may cause the AF score threshold to be adjusted. In stillother examples, more than two time periods that are not classified asnon-AF and consecutively follow a first time period classified as AF maybe required before adjusting the AF score threshold.

FIG. 11 is a flowchart 700 of a method for detecting atrialfibrillation, according to one example. At block 702, the classificationof the current time period is determined. If the classification is AF,as determined at block 704, microprocessor 224 increases the AF eventcounter at block 706 and advances to block 714 to compare a combinedcount of the AF event counter and the unclassified event counter to athreshold. If the combined counts do not meet the threshold at block714, the AF event count is compared to the AF detection threshold atblock 718. If the AF detection threshold is not reached, the processreturns to block 702 to get the next time period classification.

If the time period is not classified as AF, “No” branch of block 704,and is classified as non-AF, “Yes” branch of block 708, themicroprocessor 224 advances to block 742. The AF classificationcriteria, if previously adjusted, are restored to initial values. Forexample, if an AF score threshold has been previously adjusted to asecond lower threshold, the AF score threshold is returned to a higherfirst threshold as described in conjunction with FIG. 10. At block 746,the AF event counter and the unclassified event counter are reset tozero if they have been previously incremented to a non-zero value.

If the current time period classification obtained at block 702 isneither AF nor non-AF, i.e., if the current time period is determined tobe unclassified, “No” branch of block 708, and the AF counter iscurrently inactive with a value of zero, “No” branch of block 710,microprocessor 224 determines the classification of the next time periodat block 702. If the AF event count is greater than zero as determinedat block 710, indicating that an initial AF classification has beenmade, and the current time period is unclassified, microprocessor 224increases the unclassified event count by one at block 712. Theunclassified event count may be used for controlling adjustment of AFclassification criteria prior to an AF detection being made as describedin conjunction with FIG. 10. If the unclassified event count has reacheda predetermined threshold, “Yes” branch of block 713, microprocessor mayrestore initial AF classification criteria (if previously adjusted) atblock 742 and reset the unclassified event counter and the AF eventcounter to zero at block 746. The process begins again at block 702 withthe classification of the next time period.

After increasing the AF event count at block 706 or increasing theunclassified event count at block 712, if the unclassified event counthas not reached the predetermined threshold, “No” of block 713, thecombined event count may be compared to a threshold at block 714. Whenthe combined count of the AF event counter and the unclassified eventcounter has reached a threshold at block 714, e.g., a combined count ofthree, the AF classification criteria may be adjusted at block 716. Inone example, microprocessor 224 adjusts the AF classification criteriaby decreasing the AF score threshold to a second lower threshold afterclassifying a first time period as AF and classifying the next twoconsecutive time periods as any combination of AF or unclassified basedon the first higher AF score threshold as described above. The AFclassification criteria may therefore be adjusted in response to threeconsecutive time periods being classified as AF, a sequence of AF-U-AFor a sequence of AF-U-U.

It is to be understood that in some examples once the combined countreaches a predetermined threshold at block 714, and the AFclassification criteria have been adjusted at block 716 prior to an AFdetection being made, the AF classification criteria are not adjustedagain until AF episode termination is detected, e.g., based on a timeperiod classified as being non-AF (block 708) or based on apredetermined number of unclassified time periods (block 713), e.g.,five consecutive unclassified time periods. In other examples,additional adjustments to the AF score may be made before AF episodetermination is detected, e.g., to a third AF score threshold or back tothe first, highest AF score threshold, as described above.

At block 718, microprocessor 224 compares the AF event count to the AFdetection threshold. When the AF detection threshold has not beenreached, microprocessor 224 returns to block 702 to obtain the next timeperiod classification. As described above, after adjusting the AFclassification criteria at block 716, if a non-AF classification is made(“Yes” branch of block 708) before detecting AF, the AF classificationcriteria are restored to the initial classification criteria at block742 and all AF event and unclassified event counters are reset to zeroat block 746. If subsequent time periods are classified as AF, “Yes”branch of block 704, the AF event count is increased accordingly atblock 706.

If the AF event count reaches a detection threshold, “Yes” branch ofblock 718, microprocessor 224 detects AF at block 720. An AF detectionresponse is provided at block 721. The response to AF detection mayinclude controlling pace timing and control 212 to deliver an atrialanti-arrhythmia therapy or withhold a ventricular therapy. The responseto AF detection may additionally or alternatively include storing datarelating to the AF episode, such as the time of onset, the totalduration (as determined from the AF event counter upon detection oftermination of the AF episode as discussed below or computed using thetechniques described in conjunction with FIG. 10), storing an episode ofthe cardiac electrical signal in RAM 226 and/or other data relating tothe AF event. The data may be transmitted to external device 40 (FIG. 1)for displaying or communicating the data to a clinician for use inmanaging the patient.

When an AF detection is made at block 720, the unclassified eventcounter is reset to a count of zero at block 722. Microprocessor 224 maybegin counting subsequent time periods determined to be unclassifiedafter AF detection is made for detecting termination of the AF episode.The next time period classification is obtained at block 724. If thenext time period classification is AF, as determined at block 726, theAF event count is increased at block 728. AF classifications made afterAF detection are based on the adjusted AF classification criteria. TheAF event counter may continue to be increased with each AFclassification made after detecting AF at block 720 for use indetermining the duration of the AF episode and determining AF burden(e.g., the combined duration of all detected AF episodes over a givenmonitoring interval such as 24 hours). Such AF episode data may betransmitted to an external medical device for display or communicationto a clinician thereby providing useful information to the clinician inmaking diagnostic and therapy management decisions.

If the classification of the next time period is not AF, “No” branch ofblock 726, but is non-AF, “Yes” branch of block 730, termination of theAF episode is detected at block 740. If the classification of the nexttime period is neither AF nor non-AF, “No” branch of block 730, i.e., ifthe time period is determined to be unclassified as indicated at block732, the unclassified event counter is increased by one at block 734.The unclassified event counter is compared to a threshold at block 736.If the threshold is not reached, microprocessor 224 returns to block 724to fetch the next time period classification. If the unclassified countreaches a threshold at block 736, e.g., five consecutive unclassifiedtime periods, termination of the AF episode is detected at block 740.

If episode termination is detected, the initial AF classificationcriteria are restored at block 742, and the AF event and unclassifiedevent counters are reset at block 746. The process begins again at block702.

FIG. 12 is a flow chart 800 of a method performed by ICD 10 or ICD 110for providing a response to detecting AF according to one example. If anAF detection is made at block 802, e.g., as described in conjunctionwith any of FIGS. 9-11, an AF episode record is stored at block 804. TheAF episode record may include a Lorenz plot or histogram of RRI datathat led to AF classifications and AF detection. The episode recordstored at block 804 may further include the start time, terminationtime, and total duration of the AF episode. Referring again to FIG. 10,examples of episode durations 615, 635, 655, and 685 are shown extendingfrom the start of the first respective AF classified time period thatled to AF detection and ending with the last AF classified time periodthat leads to detection of termination of the AF episode. Unclassifiedepisodes that lead to termination detection, e.g., unclassified episodes694 and 696 in scenario (d) may not be included in the episode duration,whereas unclassified episodes that do not immediately precedetermination detection, e.g., unclassified episodes 652, 654, 656 and 658in scenario (c), are included in the episode duration, e.g., duration655.

When unclassified time periods are included in the AF episode or lead totermination detection of the AF episode, the factor(s) leading todetermining the time period as being unclassified may be stored with theAF episode record. For example, if the time period is determined to beunclassified due to other episodes being detected such as VT or VF, dueto oversensing, due to too many short RRIs, or due to too manyventricular pacing pulses during the time period, this factor may bestored to provide the clinician with useful information in diagnosingthe patient's heart rhythm status for guiding therapy decisions fortreating the patient's AF.

At block 806, microprocessor 224 may determine AF burden of the patientby computing the total time AF was identified over a 24-hour timeinterval (or other predetermined monitoring interval). Computation ofthe AF burden may include counting or summing all time periodsclassified as AF or counting or summing only AF classified time periodsthat were included in a detected AF episode. AF burden may also includeall unclassified time periods that occur during a detected AF episode.In some examples, unclassified time periods that lead to detectingtermination of the AF episode that are not included in the AF episodeduration are not included in the AF burden computation. For example,referring to FIG. 10, scenario (d), unclassified time period 684 is notincluded in AF burden computation because it occurs before the AFepisode indicated by episode duration 685. Unclassified time period 688is included in AF burden determination because it occurs during the AFepisode. Unclassified time periods 694 and 696 are not included indetermining AF burden because they lead to termination detection at time699 and are not included in the episode duration 685.

When AF is detected, microprocessor 224 may store a cardiac signalsegment that is acquired during the detected AF episode. The cardiacsignal segment is stored in memory at block 808 with the normal gain ofsense amplifiers 200 and A/D converter 222 used during cardiac signalanalysis and processing performed to identify RRIs, analyze the signalfor oversensing, etc. For example, the cardiac signal stored at block808 may be an EGM signal acquired using RV coil electrode 28 and ICDhousing 15 in FIG. 1. In system 100 of FIG. 2A, the cardiac signalstored at block 808 may be an ECG signal acquired using defibrillationelectrode 24 or defibrillation electrode 126 and housing 115. The signalstored at normal range (e.g., with 8-bit resolution sampled at 128 Hzwith A/D converter input range of ±12 mV) may be used to provide anunclipped EGM or ECG signal for morphology analysis (e.g., wavelettemplate matching) and for storing unclipped cardiac signal episodes inresponse to detecting a tachyarrhythmia. The normal range signal storedat block 808 may be selected as a far-field or relatively global cardiacelectrical signal that is used to produce a display of the electricalrhythm of the patient's heart clearly showing R-wave morphology andregularity of RRIs for the clinician to see a high level view of thesignal and the patient's corresponding rhythm. However, depending on thesensing vector, the normal range cardiac signal stored at block 808 maynot include observable or easily observed P-waves.

As such, when AF is detected, the microprocessor 224 stores a secondcardiac signal in memory at block 810 with a lower range, higher gainsetting, e.g., a range of ±2 mV which may be controlled by adjusting theA/D converter input range. The high gain, lower range setting provides aclearer view of P-waves in the stored cardiac signal segment whendisplayed by external device 40. The high gain, lower range setting mayresult in clipping of R-waves in the stored second cardiac signal.However, the first cardiac signal stored at normal range provides areliable, unclipped display of the R-wave morphology.

The second cardiac signal stored with a high gain, lower range settingmay be selected as a second far-field or relatively global signal. Forexample, in system 1 of FIG. 1, the second cardiac signal may beacquired between the RV coil electrode 24 and the SVC coil electrode 26,or the SVC coil electrode 26 to the ICD housing 15. In the system 100 ofFIG. 2A, the second cardiac signal may be acquired using the sensingelectrode 128 and sensing electrode 130, one of sensing electrodes 128,130 or 131 paired with one of defibrillation electrodes 124 or 126, orone of electrodes 124, 126, 128, 130 or 131 paired with housing 115.

When ICD 10 or ICD 110 receives an interrogation command from anexternal device 40, microprocessor 224 controls telemetry circuit 330 totransmit the AF episode record, AF burden information, and the storedfirst, normal gain cardiac signal and the second higher gain cardiacsignal. The external device is configured to generate a display of theAF data for the patient to provide the clinician with valuablediagnostic information to support therapy decision-making processes.

If AF is not being detected, “No” branch of block 802, microprocessor224 may be detecting VT or VF at block 820. If not detecting VT or VF,“No” branch of block 820, microprocessor 224 continues monitoring forcardiac tachyarrhythmias at blocks 802 and 820. If AF is not beingdetected at block 802 but microprocessor 224 is detecting VT or VF,“Yes” branch of block 820, the VT or VF episode record is stored atblock 822, which may include rate, duration, start time, end time,delivered therapies and results, etc. At block 824, a segment of thefirst cardiac signal with normal gain acquired during the detectedepisode is stored. The first cardiac signal at normal gain may be afar-field or relatively global signal as described above that provides ahigh level view of R-wave morphology and RRIs and may be the same signalwith the same gain that is stored at block 808 in response to AFdetection. At block 826, a third cardiac electrical signal is storedwith normal gain.

The third cardiac electrical signal may be a near-field or relativelylocal signal acquired with a different sensing vector than either of thefirst or second cardiac electrical signals stored at blocks 808 and 810.For example, the third cardiac signal stored at block 826 may be an EGMsignal acquired using RV tip electrode 28 and RV ring electrode 30 ofsystem 1 shown in FIG. 1. In system 100 of FIG. 2A, the cardiac signalstored at block 826 may be an ECG signal acquired using sensingelectrodes 128 and 130. The third cardiac electrical signal is storedwith normal gain but is acquired using a near-field or localizedventricular sensing vector that can be used to generate a display of ahigh quality ventricular signal when VT or VF is detected and no atrialtachyarrhythmia is detected.

In this way, ICD 10 or ICD 110 provides a unique response for storingdata depending on whether an atrial tachyarrhythmia is being detected(with or without concurrent SVT, VT or VF) or a ventriculartachyarrhythmia is being detected (without concurrent AF detection).Storage of a high gain cardiac electrical signal and transmission to anexternal device 40 for display to a clinician provides the clinicianwith valuable diagnostic information relating to the detected AFepisode. When the AF episode is being detected simultaneously with aventricular tachyarrhythmia detection, the relationship between eventsleading to the two detections can be ascertained. However, when only aventricular tachyarrhythmia is detected, storage and transmission of anear-field or localized ventricular signal may provide the clinicianwith important information regarding the ventricular rhythm.

In some examples, microprocessor 224 responds to an AF detection byselecting which cardiac electrical signals are stored as described aboveand transmits the signals with normal gain and range to external device40. Processor 52 of external device 40 may automatically generate adisplay on user display 54 that includes the first, high gain, low rangesignal for observation of P-waves and the second, normal gain, normalrange signal for unclipped observation of R-waves.

FIG. 13 is a flow chart 900 of a method performed by an implantablemedical device system, such as a system including ICD 10 and lead 16 orICD 100 and lead 116, for automatically adjusting a detection thresholdrequired to detect an atrial tachyarrhythmia, such as AF. The detectionthreshold may be a minimum time duration that the cardiac electricalsignal received by sensing circuitry of the ICD must correspond to, orbe classified as, the atrial tachyarrhythmia in order to detect theatrial tachyarrhythmia episode. This detection threshold may be definedas a time interval in some atrial tachyarrhythmia detection algorithms.In other examples, the detection threshold may be defined as a thresholdnumber of time predetermined periods required to be classified as AF inorder to detect an AF episode, e.g., as generally described inconjunction with FIGS. 9, 10 and 11. In the illustrative examplesprovided herein, the time periods are two minutes long and the thresholdnumber of time periods that are required to be classified as AF in orderto detect an AF episode is three time periods. In other words, a totaltime duration of at least six minutes of the cardiac electrical signalneeds correspond to AF, e.g., be classified as AF based on an AF scoreand other factors, in order to detect AF. The six minutes are notnecessarily consecutive since one or more two-minute time periods thatare unclassified may occur between the three time periods classified asAF. In the flow chart of FIG. 13, the microprocessor 224 of ICD 10 or110 may automatically adjust the detection threshold by adjusting thenumber of time periods classified as AF that are required in order todetect an AF episode. For example, microprocessor 224 may be configuredto automatically adjust the detection threshold by adjusting a countthreshold applied to the AF event counter that is used to count thenumber of time periods that are classified as AF (see blocks 706 and 718of FIG. 11).

At block 902, microprocessor 224 may set an initial detection threshold.For example, the initial detection threshold may be three two-minutetime periods, for a total time duration of six minutes of the cardiacelectrical signal being classified as AF. The detection threshold maygenerally represent the minimum duration of time that the cardiac signalis required to present an AF rhythm and, depending on the particular AFdetection algorithm implemented in the ICD 10 or 110, may be expressedas a time interval, e.g., 6 minutes, rather than the value of an AFevent counter that counts the number of time periods classified as AF.The initial detection threshold may be set to a relatively low value inorder to achieve a relatively high sensitivity for detecting AFepisodes. In this way, a patient that is unknown to experience AF, orthe characteristics of the AF or AF burden are unknown for a givenpatient, AF episodes will be detected with relatively high sensitivityinitially, e.g., beginning after ICD implantation.

The processor 224 ICD 10 or 110 monitors the heart rhythm at block 904according to the implemented AF detection algorithm using the initialdetection threshold. For example, the heart rhythm may be monitoredaccording to the techniques described above in conjunction with FIGS.5-11 for detecting an AF episode based on the initial detectionthreshold of n time periods (e.g., three time periods) being classifiedas AF. If AF is detected at block 906 based on the initial detectionthreshold, “yes” branch of block 906, an AF episode counter is increasedat block 908.

Microprocessor 224 determines if detection threshold adjustment criteriaare met at block 910. This determination may be made by comparing the AFepisode counter to an AF monitoring threshold count at block 910. If thecount of AF episodes detected based on the initial detection thresholdhas not reached the AF monitoring threshold count at block 910, the ICDcontinues monitoring the heart rhythm at block 904 using the initialdetection threshold.

In one example, the AF monitoring threshold count applied at block 910is a count of three AF episodes detected based on the initial detectionthreshold. If the AF episode count has not reached a value of threedetected AF episodes, the heart rhythm continues to be monitored atblock 904 using the initial detection threshold. A relatively sensitiveAF detection threshold, e.g., a relatively short total time duration ornumber of time periods classified as AF continues to be used fordetecting AF episodes for identifying how likely the patient is toexperience AF and how often.

In other examples, the detection threshold adjustment criteria appliedto detected AF episodes at block 910 may include a frequency and/orduration of detected AF episodes. For instance, a threshold count may berequired to be reached within a predetermined time period. In oneexample, at least five AF episodes may be required to be detected within30 days in order for the detection threshold adjustment criteria to besatisfied at block 910. In another example, at least one detected AFepisode may be required to have an episode duration that is greater thana predetermined threshold duration, e.g., at least 10 minutes. In yetanother example, the detection threshold adjustment criteria applied atblock 910 may be based on an AF burden threshold. For example, thecriteria at block 910 may require that the summed episode durations ofAF episodes detected based on the initial detection threshold within apredetermined time period meets an AF burden threshold. For instance,the summed episode durations of detected AF episodes may be required toreach a cumulative duration of at least 15 minutes within a 24-hourperiod.

The detection threshold adjustment criteria may include multiplecriteria, and when any one of the criterion are met, the detectionthreshold may be adjusted. In one example, the adjustment criteria mayinclude a first threshold number of detected AF episodes, a secondthreshold number of episodes detected within a predetermined timeinterval, a threshold episode duration, and/or a threshold AF burden. Ifany one of these thresholds is reached, the detection threshold may beadjusted. To illustrate, the detection threshold adjustment criteria maybe met if the AF episode counter reaches a total count of 5 detected AFepisodes; if the AF episode counter reaches a count of 3 detected AFepisodes within 30 days; if a detected AF episode has an episodeduration of at least 10 minutes; or if the AF burden has reached atleast 15 minutes of cumulative AF episode durations within 24 hours. Thenumber of detected AF episodes, the frequency of detected AF episodes,the maximum episode duration of detected AF episodes, and/or the AFburden may be used alone or in any combination for determining ifdetection threshold adjustment are met at block 910. The example valuesof the thresholds given above are intended to be illustrative in naturewith no limitation intended. Numerous other examples of combinations ofmultiple criteria and corresponding threshold values may be conceivedbased on the examples given herein.

If the detected AF episodes satisfy the detection threshold adjustmentcriteria at block 910, microprocessor 224 adjusts the detectionthreshold at block 912. The detection threshold may be adjusted to avalue that is greater than or less than the initial detection threshold.In one example, the detection threshold is adjusted to reduce thesensitivity to detecting AF by increasing the minimum time duration ornumber of AF-classified time periods that are required to detect an AFepisode. For instance, if the initial detection threshold is threetwo-minute time periods, the adjusted detection threshold may be fivetwo-minute time periods required to be classified as AF in order todetect an AF episode. The reduced sensitivity to AF detection may avoidfalse AF detection and reduce the number of AF episodes for which datais stored in memory of the ICD that requires review or verification by aclinician, easing clinician burden while still capturing important AFepisode data.

At block 914, ICD 10 or 110 monitors the heart rhythm for detecting AFaccording to the implemented AF detection scheme, e.g., as described inconjunction with FIGS. 5 through 11, using the adjusted detectionthreshold. The longer time duration of the AF detection threshold (e.g.,five two-minute time periods instead of three two-minute time periods)may reduce the sensitivity of AF detection but may increase thespecificity of AF detection for long-term monitoring of the patient.

In other examples, the AF detection threshold may be adjusted to a lowervalue at block 912 that increases AF detection sensitivity. In somecases, a clinician may prefer AF detection episodes be detected withgreater sensitivity once AF is identified in a given patient based on aless sensitive AF detection threshold. In this case, the AF detectionthreshold may be reduced to a shorter total time duration, or fewer timeperiods classified as AF, in order to detect an AF episode.

Microprocessor 224 may execute a response to detecting an AF episode atblock 915. The response to an AF episode detection may include one ormore of storing AF episode data which may include a segment of thecardiac electrical signal received during the detected AF episode,updating an AF burden, withholding, delaying or adjusting a therapy,and/or withholding delaying or adjusting a ventricular tachyarrhythmiadetection.

FIG. 14 is a flow chart 920 of a method for automatically adjusting adetection threshold for detecting AF according to another example.Blocks 902 through 912 correspond to identically-numbered blocks of FIG.13. After adjusting the detection threshold at block 912 in response toone or more AF episodes detected based on the initial detectionthreshold satisfying the detection threshold adjustment criteria atblock 910, a monitoring period is started at block 916. The monitoringperiod may be a predetermined time period used to control how long thedetection threshold remains at the adjusted value. The monitoring periodmay be a predetermined number of hours, days or weeks. In one example,the monitoring period is 90 days.

At block 922, the heart rhythm is monitored according to the implementedAF detection techniques, e.g., as described above in conjunction withFIGS. 5 through 11. If an AF episode is detected causing the AF episodecounter to be increased, “yes” branch of block 924, microprocessor 224may determine if second detection threshold adjustment criteria are metat block 928. If the second detection threshold adjustment criteria arenot satisfied at block 928, the microprocessor returns to block 922 tocontinue monitoring the heart rhythm using the detection threshold setat block 912.

During the monitoring period, however, the AF detection threshold may beadjusted from the detection threshold set at block 912 when the numberand/or frequency of AF episode detections made based on the adjusteddetection threshold satisfy second threshold adjustment criteria atblock 928. For instance, if the AF episode counter reaches a count oftwo AF episodes detected using the adjusted AF detection threshold, theAF detection threshold may be adjusted again at block 930. In anotherexample, the second detection threshold adjustment criteria applied atblock 928 may require that at least two AF episodes are detected withina predetermined time period that is shorter than the monitoring period,e.g., two AF episode detections within thirty days. If the requiredfrequency of AF episode detections occurs during the monitoring period,the AF detection threshold is adjusted at block 930. The seconddetection threshold adjustment criteria may require a threshold count ofAF episode detections based on the adjusted detection threshold, athreshold frequency of AF episode detections based on the adjusteddetection threshold, an AF episode duration equal to or greater than aduration threshold, an AF burden equal to or greater than an AF burdenthreshold, or any combination thereof.

The AF detection threshold may be adjusted to be less sensitive toincrease the specificity of AF detection. For instance, the total timeduration required to detect AF may be increased, e.g., from 10 minutesor 5 two-minute time periods classified as AF to 20 minutes or 10two-minute time periods classified as AF. After adjusting the AFdetection threshold at block 930, the microprocessor 224 returns toblock 916 to start a new monitoring period. The AF episode counter usedto track the number of AF episodes detected during a monitoring periodmay be reset to zero. The microprocessor 224 continues to monitor theheart rhythm at block 922 using the most recently adjusted AF detectionthreshold.

In some examples, in addition to or alternatively to adjusting the totaltime duration or number of time periods classified as AF at block 930,the AF score threshold may be adjusted at block 930. The AF scorethreshold may be set to first and second values as described inconjunction with FIG. 10 as two-minute time periods are beingclassified. One or both of the first AF score threshold 602 and thesecond AF score threshold 604 (shown in FIG. 10) may be adjusted atblock 930 for use in classifying a two-minute time period. For example,the AF score threshold may initially be set to a first threshold 602 of50 for classifying an initial time period as AF and reduced to a secondthreshold 604 of 38. At block 930, the AF score threshold may beincreased to less sensitive settings where the first threshold 602 isset to 60 and the second threshold 604 is set to 45.

If the monitoring period expires (“yes” branch of block 926) before anyAF episodes are detected based on the adjusted AF detection threshold(“no” branch of block 924), the microprocessor 224 returns to block 912and resets the detection threshold (if previously adjusted at block 930)to the previous detection threshold used for chronic monitoring at block912. For example, if a second adjustment of the AF detection thresholdis made at block 930 and a new monitoring period is started at block916, but the monitoring period expires at block 926 with no AF episodesbeing detected during the monitoring period, the AF detection thresholdis returned to the first adjusted value set at block 912. In theillustrative example given above, an initial detection threshold may be6 minutes set at block 902, which is adjusted to 10 minutes at block912, and may be adjusted again to 20 minutes at block 930. If no AFepisodes are detected during a monitoring period when the AF detectionthreshold corresponds to a total time duration of 20 minutes of thecardiac electrical signal being classified as AF, the AF detectionthreshold may be adjusted back to the 10 minute duration (e.g., 5two-minute time periods classified as AF).

In some cases, the AF detection threshold is adjusted back to thepreceding AF detection threshold value if the monitoring period expiresat block 926. Continuing with the illustrative example given above, ifthe AF detection threshold is currently set at 10 minutes or 5two-minute time periods classified as AF, the AF detection threshold isadjusted back to 6 minutes or 3 two-minute time periods. In otherexamples, instead of returning to block 912 when the monitoring periodexpires with no AF detection, the process may return to block 902 to setthe detection threshold to the initial value, e.g., 6 minutes or 3two-minute time periods in the example given above.

While not explicitly shown in flow chart 920 of FIG. 14, it is to beunderstood that upon detecting an AF episode at block 906 and/or block924, microprocessor 224 may control the ICD to provide a response to AFepisode detection as described above in conjunction with block 915 ofFIG. 13 or any of the AF episode detection responses described inconjunction with block 721 of FIG. 11.

FIG. 15 is a flow chart 950 of a method for detecting AF and determiningAF burden by a cardiac medical device according to another example. Thetechniques described above for adjusting the AF detection threshold maybe used to control detection of AF episodes for providing a response ofstoring AF episode data such as a cardiac signal segment, e.g., asdescribed in conjunction with FIG. 12. Other AF episode detectionresponses, however, may be made by ICD 10 or ICD 110 based on adifferent AF detection threshold, which may not be automaticallyadjustable. Other responses to detecting an AF episode that may be madeby ICD 10 or ICD 110 may include determining AF burden. AF burden may bedetermined by summing the AF episode durations for all AF episodesdetected over a 24 hour period or other predetermined time period. Insome cases, a different AF detection threshold is used for detecting AFepisodes for determining AF burden than the AF detection threshold thatis used for detecting AF episodes for which a cardiac electrical signalsegment is stored.

In flow chart 950, the blocks 902, 904, 906, 908 and 910 correspond toidentically numbered blocks described above in conjunction with flowchart 900 of FIG. 13. However, in addition to determining whetherdetection threshold adjustment criteria are met at block 910 afterincreasing the AF episode count at block 908, the AF burden may beupdated by microprocessor 224 at block 909 by summing the duration ofthe AF episode detected at block 906 with the episode durations of anyAF episodes detected previously within a predetermined AF burden timeinterval. For example, the AF burden may be determined and stored foreach consecutive 24 hour time interval or for a running 24 hour timeinterval. In other examples, the AF burden may be determined overanother moving predetermined time interval.

If the detection threshold adjustment criteria are met at block 910, asdescribed above in conjunction with FIG. 13, the detection threshold forAF episode storage is adjusted at block 952. The adjustment to thedetection threshold at block 952 may be an increase in the total timeduration, e.g., defined as the number of two-minute time periodsclassified as AF as described above in conjunction with FIGS. 13-14. Forexample, the detection threshold used for triggering AF episode storagemay be adjusted from 6 minutes (or 3 two-minute time periods) to 10minutes (or 5 two-minute time periods) of the cardiac electrical signalbeing classified as AF.

The detection threshold used for updating the AF burden, however, may bekept the same as the initial detection threshold set at block 902 oradjusted to a detection threshold different than the detection thresholdset at block 952 for AF episode storage. The detection threshold forupdating the AF burden is set at block 954. In some cases, the detectionthreshold for updating AF burden is set or maintained at a moresensitive setting than the detection threshold set at block 952 forepisode storage. For example, the detection threshold for updating AFburden may be kept at 6 minutes or a count of 3 two-minute time periodsclassified as AF, and the detection threshold set at block 952 forepisode storage is set to a relatively less sensitive setting of 10minutes or a count of 5 two-minute time periods classified as AF. Inthis way, the AF burden is determined with relatively high sensitivityand relatively low specificity while AF episodes that may be stored forreview by a clinician are detected with relatively higher specificityand relatively lower sensitivity than the AF episodes detected forupdating the AF burden.

When an AF episode is detected at block 956 based on the detectionthreshold set at block 954 (or kept the same as the initial detectionthreshold), the duration of the detected episode is determined at block958. The duration of the detected episode may be determined using themethods described above in conjunction with FIGS. 9 and 10.Microprocessor 224 updates the AF burden at block 960 using thedetermined episode duration. The episode duration may be summed with theduration(s) of previous AF episode(s) that have been detected since thestart of the AF burden time period, e.g., since the start of a 24-hourtime period.

The process of updating the AF burden at block 960 continues byreturning to block 956 to wait for the next AF episode detected based onthe detection threshold set at block 954. The detection threshold usedfor detecting AF episodes used to update the AF burden may not beautomatically adjusted by microprocessor 224 in some examples and mayremain fixed at the initial detection threshold set at block 902 or setto a user-programmed value. In other examples, the detection thresholdused for updating AF burden may be adjusted once at block 954 from theinitial detection threshold set at block 902 after the detectionthreshold adjustment criteria are met at block 910 and not adjustedagain. In still other examples, the detection threshold used forupdating the AF burden, storing AF episode data such as a cardiacelectrical signal segment and/or providing other responses to AFdetection by ICD may be adjusted to desired values based on adjustmentcriteria being met in the manner described above in conjunction withFIGS. 13 and 14.

In the example of FIG. 15, however, the detection threshold is adjustedat block 952 to a relatively less sensitive setting than the AFdetection threshold set at block 954 for updating AF burden. Theadjusted detection threshold value set at block 652 is used fordetecting AF episodes for which a cardiac signal segment is to be storedin RAM 226 (or other computer-readable storage media such as theexamples given previously herein). Blocks 916, 922, 924, 926 and 928 offlow chart 950 may correspond to identically-numbered blocks describedabove in conjunction with FIG. 14. In the process of flow chart 950,microprocessor 224 may be configured to provide a response to an AFepisode detected at block 924 by updating stored AF episode data atblock 925. Methods for updating AF episode data stored in RAM 224 of ICD10 or 110 are described below in conjunction with FIG. 16.

At block 960, the detection threshold may be adjusted when second AFdetection threshold adjustment criteria are met at block 928. Theadjustment performed at block 960 may correspond to the adjustmentdescribed in conjunction with block 930 of FIG. 14, e.g., to a lesssensitive setting for detecting AF, but in the example of FIG. 15, thedetection threshold that is adjusted at block 960 is applied only fordetecting AF episodes that trigger AF episode data storage at block 925and is not used for detecting AF episodes that trigger other AFdetection responses, such as causing the AF burden to be updated.

FIG. 16 is a flow chart 980 of a method for responding to AF episodedetection by storing AF episode data according to one example. At block982, an AF episode is detected. The detection of the AF episode at block982 may be based on an initial AF detection threshold, e.g., a detectionmade at block 906 based on the initial detection threshold set at block902 of any of FIG. 13, 14 or 15. In other instances, the detection ofthe AF episode at block 982 may be an AF detection made based on anadjusted AF detection threshold during heart rhythm monitoring at block914 of FIG. 13. The process of flow chart 980 for updating detected AFepisode storage may be performed at block 915 of FIG. 13.

In other examples, the detection of the AF episode at block 982 is an AFdetection made at block 924 in response to an adjusted AF detectionthreshold as described above in conjunction with FIGS. 14 and 15. Inother words, the process for updating AF episodes stored in the memoryof the ICD 10 or 110 according to the flow chart 980 may be performedany time AF is detected based on an initial AF detection thresholdand/or based on an AF detection threshold that has been adjusted for AFmonitoring and AF episode storage. It is to be understood that an AFepisode detected at block 956 based on an AF detection threshold setspecifically for updating AF burden as described in conjunction withFIG. 15, may be ignored at block 982 of FIG. 16 when a different AFdetection threshold has been set for triggering AF episode data storage.

At block 984, the duration of the AF episode detected at block 982 isdetermined. For example, the AF episode duration may be determined atblock 984 using any of the methods described above in conjunction withFIG. 10. At block 986, microprocessor 224 determines if memory binsallocated for AF episode storage are full. If not, a cardiac signalsegment acquired during the detected AF episode is stored in ICD memory,e.g., RAM 226, at block 992. In some examples, a predetermined number ofbins may be allocated for multiple AF episode durations or episodeduration ranges. Each episode duration or duration range may havemultiple bins allocated for storing episodes of that specific durationor duration range. For example, three bins may be allocated for storingAF episodes having an episode duration that is equal to or greater thanan initial detection threshold but less than an adjusted detectionthreshold and three bins may be allocated for storing AF episodes havinga duration that is equal to or greater than the adjusted detectionthreshold.

In the examples given above, three bins may be allocated for storingcardiac electrical signal segments acquired during AF episodes having anepisode duration that is at least the initial detection threshold of 6minutes or 3 two-minute time periods but less than the adjusteddetection threshold of 10 minutes or 5 two-minute time periods. Threeother bins may be allocated for storing cardiac electrical signalsegments that are acquired during an AF episode having an episodeduration that is at least the adjusted detection threshold of 10 minutesor 5 two-minute time periods. In this way, a cardiac electrical signalsegment may be stored for each of up to three AF episodes detected usingthe 6 minute detection threshold and having an episode duration that isless than 10 minutes and cardiac electrical signal segments may bestored for each of up to three AF episodes having an episode durationthat is equal to or greater than 10 minutes, regardless of the detectionthreshold used to detect the AF episode.

In other examples, memory bins may be allocated according to thedetection threshold used to detect the AF episode. For example, threebins may be allocated for storing a cardiac electrical signal segmentacquired during an AF episode detected based on the initial detectionthreshold, and three bins may be allocated for storing a cardiacelectrical signal segment acquired during an AF episode detected basedon an adjusted detection threshold. Additional bins may be allocated foreach detection threshold used when two or more adjustments to thedetection threshold are made.

The episode duration determined at block 984 may be used to determinewhich bin the cardiac electrical signal segment is written to at block992. The cardiac electrical signal segment is written to a bin allocatedto an episode duration or range matching or including the determinedepisode duration. In other examples, the detection threshold used todetect the AF episode is used to determine which bin the cardiacelectrical signal segment is written to at block 992. The cardiacelectrical signal segment is written to a bin allocated to the detectionthreshold used to detect the AF episode.

If the bins allocated to the corresponding AF episode duration ordetection threshold are not full, “no” branch of block 986, the cardiacelectrical signal segment is written to any of the unoccupied binsallocated for that AF episode duration or detection threshold. If thebins allocated for the corresponding episode duration or detectionthreshold are full, “yes” branch of block 986, microprocessor 224determines at block 988 if the currently detected AF episode has anepisode duration that is longer than any currently stored AF episodes.If a cardiac electrical signal segment is stored for an AF episodehaving a longer episode duration than the most recently detected AFepisode, the data stored for the longest duration AF episode is notoverwritten as indicated at block 990. Another occupied bin allocated tothe corresponding duration or detection threshold of the most recentlydetected AF episode is overwritten at block 992 to store the cardiacelectrical signal segment corresponding to the most recently detected AFepisode. The bin that is overwritten may be the bin storing the oldestAF episode data such that the cardiac electrical signal segments (andany other AF episode data) are stored in a first-in-first-out basis withthe exception of retaining AF episode cardiac signal segment stored forthe longest duration AF episode, regardless of age by not overwritingthe data stored for the longest duration AF episode when a newer AFepisode is detected. In this way, data for both the most recentlyoccurring AF episodes and data for the AF episode having the longestepisode duration, regardless of how long ago the longest episode wasdetected, are accumulated in ICD memory.

If the most recently detected AF episode has a longer episode durationthan any of the stored episodes, “yes” branch of block 988, a cardiacelectrical signal segment is stored at block 992 by overwriting theoldest data in a bin allocated for the corresponding episode duration ordetection threshold. It is recognized that when ICD 10 or 110 isinterrogated by an external device, e.g., external device 40 (shown inFIG. 1), data stored in all bins may be transmitted to the externaldevice and all bins allocated for storing AF episode data may becleared.

When the method of FIG. 16 is used to control storing of cardiac signalsegments in response to AF episode detection, the AF episodes detectedusing the adjusted AF detection threshold that has been increased toachieve relatively higher specificity and relatively lower sensitivitypromotes storage of true AF episodes. The likelihood of storing datacorresponding to false AF episodes is reduced, thereby reducing theburden placed on a clinician in reviewing AF episode data that does notcorrespond to true AF episodes.

While the examples disclosed herein refer primarily to the detection ofAF, it is contemplated that aspects of the techniques of the presentdisclosure may be utilized for detecting and responding to other atrialtachyarrhythmia episodes, such as atrial flutter and atrial tachycardia.

Thus, an apparatus and methods have been presented in the foregoingdescription for detecting and responding to atrial tachyarrhythmia withreference to specific examples. It is appreciated that variousmodifications to the referenced examples may be made, includingmodifying the order of steps performed and/or modifying the combinationsof operations shown in the flow charts presented herein, withoutdeparting from the scope of the following claims.

1. A medical device system for detecting an atrial tachyarrhythmiaepisode, comprising: sensing circuitry configured to receive a cardiacelectrical signal from a plurality of electrodes coupled to the sensingcircuitry; and a processor configured to: detect a first atrialtachyarrhythmia episode in response to a time duration of the cardiacelectrical signal classified as an atrial tachyarrhythmia being greaterthan or equal to a first detection threshold; determine if detectionthreshold adjustment criteria are met based on at least the detectedfirst atrial tachyarrhythmia episode; and adjust the first detectionthreshold to a second detection threshold different than the firstdetection threshold in response to the detection threshold adjustmentcriteria being met.
 2. The system of claim 1, wherein the processor isconfigured to detect the first atrial tachyarrhythmia episode by:identifying R-waves in the cardiac electrical signal attendantventricular depolarizations; determining classification factors from theR-waves identified over a plurality of predetermined time periods;classifying each of the plurality of predetermined time periods as oneof atrial tachyarrhythmia, non-atrial tachyarrhythmia or unclassifiedbased on comparing the determined classification factors toclassification criteria; and detecting the atrial tachyarrhythmiaepisode in response to the plurality of predetermined time periods thatare classified as atrial tachyarrhythmia reaching a threshold number oftime periods.
 3. The system of claim 1, wherein the processor is furtherconfigured to adjust the detection threshold by increasing a timeduration threshold that the duration of the cardiac electrical signalclassified as the atrial tachyarrhythmia must be equal to or greaterthan in order to detect the atrial tachyarrhythmia.
 4. The system ofclaim 1, wherein: the detection threshold adjustment criteria comprise apredetermined time duration threshold that is longer than the firstdetection threshold; and the processor is configured to determine thatthe detection threshold adjustment criteria are met by: determining anepisode duration of the first atrial tachyarrhythmia episode, comparingthe episode duration to the predetermined time duration threshold; anddetermining that the detection threshold adjustment criteria are metbased on the episode duration being equal to or greater than thepredetermined time duration threshold.
 5. The system of claim 1,wherein: the detection threshold adjustment criteria comprise apredetermined number of atrial tachyarrhythmia episodes being detectedbased on the first detection threshold; and the processor is furtherconfigured to determine that the detection threshold adjustment criteriaare met by: determining a count of atrial tachyarrhythmia episodes thatare detected based on the first detection threshold; and determiningthat the detection threshold adjustment criteria are met in response tothe count reaching the predetermined number.
 6. The system of claim 7,wherein the processor is further configured to determine that thedetection threshold adjustment criteria are met in response to the countreaching the predetermined number within a predetermined time period. 7.The system of claim 1, wherein the processor is further configured todetermine that the detection threshold adjustment criteria are met inresponse to at least one of: the first atrial tachyarrhythmia episodedetected based on the first detection threshold having an episodeduration that is greater than a predetermined episode duration; a firstpredetermined number of atrial tachyarrhythmia episodes being detectedbased on the first detection threshold; a second predetermined number ofatrial tachyarrhythmia episodes being detected based on the firstdetection threshold within a predetermined time period; or an atrialtachyarrhythmia burden exceeding an atrial tachyarrhythmia burdenthreshold, the processor configured to determine the atrialtachyarrhythmia burden by summing a plurality of episode durationsdetermined from a plurality of atrial tachyarrhythmia episodes detectedbased on the first detection threshold.
 8. The system of claim 1,wherein the processor is further configured to: adjust the seconddetection threshold back to the first detection threshold in response toa predetermined time period expiring without detecting an atrialtachyarrhythmia episode based on the second detection threshold.
 9. Thesystem of claim 1, wherein the processor is further configured to:detect at least one atrial tachyarrhythmia episode based on the seconddetection threshold; determine if second detection threshold adjustmentcriteria are met in response to the at least one atrial tachyarrhythmiaepisode detected based on the second detection threshold; and adjust thesecond detection threshold to a third detection threshold greater thanthe second detection threshold in response to the second detectionthreshold adjustment criteria being met.
 10. The system of claim 1,further comprising: a memory coupled to the processor; and a telemetrycircuit coupled to the processor and memory and configured to transmitcardiac electrical signal data stored in the memory to an externaldevice; wherein the processor is configured to: store in the memory asegment of the cardiac electrical signal received during the firstatrial tachyarrhythmia episode; and control the telemetry circuit totransmit the segment to the external device for generating a display ofthe cardiac electrical signal segment.
 11. The system of claim 1,further comprising a memory coupled to the processor, wherein theprocessor is further configured to: detect a second atrialtachyarrhythmia episode based on a second time duration of the cardiacelectrical signal classified as the atrial tachyarrhythmia being equalto or greater than the second detection threshold; store in the memory asegment of the cardiac electrical signal in response to detecting thesecond atrial tachyarrhythmia episode.
 12. The system of claim 1,wherein the processor is further configured to: set a third detectionthreshold; monitor for atrial tachyarrhythmia episodes based on thethird detection threshold concurrently with monitoring for atrialtachyarrhythmia episodes based on the second detection threshold;determine an atrial tachyarrhythmia burden in response to detecting anatrial tachyarrhythmia episode based on the third detection threshold;and store a segment of the cardiac electrical signal received during anatrial tachyarrhythmia episode detected based on the second detectionthreshold.
 13. The system of claim 1, further comprising a memorycoupled to the processor, wherein the processor is further configuredto: allocate a plurality of memory bins of the memory to each one of aplurality of episode duration ranges; determine a first episode durationof the first atrial tachyarrhythmia episode; store a segment of thecardiac electrical signal received during the first atrialtachyarrhythmia episode in one of the plurality of memory bins allocatedto one of the episode duration ranges that includes one of the firstepisode duration or the first detection threshold; detect a secondatrial tachyarrhythmia episode based on a second time duration of thecardiac electrical signal classified as the atrial tachyarrhythmia beingequal to or greater than the second detection threshold; determine asecond episode duration of the second atrial tachyarrhythmia episode;and store a second segment of the cardiac electrical signal receivedduring the second atrial tachyarrhythmia episode in one of the pluralityof memory bins allocated to one of the episode duration ranges thatincludes one of the second episode duration or the second detectionthreshold.
 14. The system of claim 13, wherein the processor is furtherconfigured to: compare the second episode duration to a longest episodeduration of atrial tachyarrhythmia episodes previously detected based onone of the first detection threshold or the second detection threshold;store the second segment in one of the plurality of memory bins notcurrently occupied by a third segment of the cardiac electrical signalstored during the longest episode duration.
 15. The system of claim 1,comprising an implantable cardioverter defibrillator and a transvenouslead coupled to the implantable cardioverter defibrillator and carryingat least one transvenous electrode, the sensing circuitry receiving thecardiac electrical signal via the at least one transvenous electrode,the implantable cardioverter defibrillator comprising a housingenclosing the sensing circuitry and the processor.
 16. The system ofclaim 1, comprising an implantable cardioverter defibrillator and anextra-cardiovascular lead coupled to the implantable cardioverterdefibrillator and carrying at least one extra-cardiovascular electrode,the sensing circuitry receiving the cardiac electrical signal via the atleast one extra-cardiovascular electrode, the implantable cardioverterdefibrillator comprising a housing enclosing the sensing circuitry andthe processor.
 17. The system of claim 1, wherein the processor isfurther configured to provide a response to the detection of the atrialtachyarrhythmia episode, the response comprising at least one of:controlling therapy circuitry within the system to withholding atherapy, adjusting a therapy, or deliver a therapy; controlling apatient notification system to generate a patient alert; transmittingdata via telemetry circuit to alert a clinician or a patient; and/ortriggering a second signal acquisition or analysis.